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Speaker 1: We've all heard of Adobe's PDF format, the file format

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Speaker 1: that lets you share and present documents without worrying about

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Speaker 1: the software, hardware or operating system being used.

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Speaker 2: But have you heard about the Kiwi company that has

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Speaker 2: racked up one hundred million users worldwide with its PDF

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Speaker 2: editing tools. It's an under the radio success story that's

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Speaker 2: leveraging big platforms like Microsoft three sixty five and Google

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Speaker 2: Drive to take software to the world.

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Speaker 1: It's also a pretty incredible tale of a company that

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Speaker 1: basically threw out its existing product and replaced it from

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Speaker 1: the ground up just in time for the pandemic to arrive.

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Speaker 3: We kind of got rid of like all the code

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Speaker 3: were written beforehand and we just started from scratch. That

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Speaker 3: kicked off a year and a half journey where we

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Speaker 3: rebuilt everything that was woman and then release that in

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Speaker 3: twenty nineteen. I can say it was a huge amount

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Speaker 3: of stress kind of leading up to that, especially those

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Speaker 3: last few weeks where you realize you're effectively going to

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Speaker 3: turn off the entire service, which at the time probably

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Speaker 3: thirty forty more than people using it.

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Speaker 1: I'm Peter Griffin, I'm Ben Moore, and on the Business

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Speaker 1: of Tech Powered by a two degrees. Business this week

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Speaker 1: is Max Ferguson, founder of christ Church based software as

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Speaker 1: a service company Lumen.

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Speaker 2: It's just over ten years since Max started Lumen. As

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Speaker 2: so many startups, begin in a dorm room at Stanford University.

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Speaker 2: It's now probably one of the most widely used New

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Speaker 2: Zealand made software products around.

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Speaker 1: You've probably used it yourself at some point as an

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Speaker 1: alternative to Adobe acrobats product to edit a PDF. But

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Speaker 1: as Max explains, Luman has evolved well beyond a pdf editor.

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Speaker 2: Yeah, it's very much becoming a platform for signing documents,

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Speaker 2: collaborating with documents, verifying your identity as contracts and forms

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Speaker 2: get easier to deal with online. So the interview with

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Speaker 2: Max coming up. But first Ben, we need to gauge

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Speaker 2: the lay of the land on deep Seek and look

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Speaker 2: at some AI developments out of our own government. Here.

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Speaker 1: Well, the AI conversation continues, and I think the world

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Speaker 1: has definitely shifted this year in that regard with Deep Seek,

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Speaker 1: and I think just the attitudes to China more broadly,

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Speaker 1: with everything that's going on with TikTok and some of

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Speaker 1: the stuff coming out of the US that has ground

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Speaker 1: people's gears a little bit. Obviously, when deep Seek first

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Speaker 1: exploded onto the scene, there was a flurry of interest

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Speaker 1: and excitement and discussion, and then slowly, over the next

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Speaker 1: couple of weeks there's been a real questioning of some

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Speaker 1: of the narrative and some kind of people trying to

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Speaker 1: figure out what it actually means. So, Peter, what are

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Speaker 1: you hearing or reading about with the actual application of

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Speaker 1: some of what deep seek has done.

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Speaker 2: Yeah, well, you know, people have been pouring over deep Seek.

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Speaker 2: Those who really are close to the AI large language

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Speaker 2: model world been pouring over it since late December. Anyway.

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Speaker 2: That was the V three model, then the R one

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Speaker 2: model that have come out, and really, you know, it

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Speaker 2: stacks up. So a lot of the experts are saying

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Speaker 2: that it really is quite ingenious. There's a lot of creativity.

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Speaker 2: There's a lot of innovation that has happened. Because it's

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Speaker 2: open source, they can literally get down into the weeds

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Speaker 2: and look at it, how it works. It's got a

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Speaker 2: very generous licensing arrangement around it, the MIT licensing schemes.

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Speaker 2: So people are running it. I've been running it on

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Speaker 2: my laptop. I know lots of people in New Zealand

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Speaker 2: who are experimenting with it. It's already built into Perplexity pro,

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Speaker 2: so I'm using it on a day to day basis.

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Speaker 2: That's how quickly it's been embraced. And this is obviously

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Speaker 2: the not the censored version, the web based version that

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Speaker 2: is available as an app and went to the top

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Speaker 2: of the app store last week. This is the model

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Speaker 2: that you can take away, build on top of, adapt

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Speaker 2: the code base, and have the pure sort of R

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Speaker 2: one experience. So I think the first thing is the

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Speaker 2: technical experts are sort of an agreement that there's some

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Speaker 2: really cool stuff going on here. There's maybe a question

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Speaker 2: mark over the actual costs of the training, how much

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Speaker 2: computing capacity was applied to this, to what extent it

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Speaker 2: relied on other models, maybe open AIS models to help

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Speaker 2: train R one and V three. So still some question marks,

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Speaker 2: but you know, a big win for China. And I

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Speaker 2: think the second thing is the just how it's sort

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Speaker 2: of turbocharging this sort of anxiety about the race between

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Speaker 2: China and the US for AI supremacy. And there's been

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Speaker 2: lots of people sort of dialing back those concerns or

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Speaker 2: trying to because we're in sort of result seasons for

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Speaker 2: some of these big AI companies like Meta and Mark

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Speaker 2: Zuckerberg really doubled down, tried to cam things down, said

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Speaker 2: we're forging ahead with our sixty five billion dollar investment

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Speaker 2: and data center infrastructure. You Microsoft is saying the same thing,

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Speaker 2: So they're basically trying to tell the market this doesn't

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Speaker 2: undermine our business model. We think all of this investment

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Speaker 2: is still warranted. And I think they probably have a

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Speaker 2: good argument there. But in the back of their minds

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Speaker 2: and in those companies, you know, apparently Meta has set

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Speaker 2: up a war room to look into deep seek and

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Speaker 2: what the implications of it are. They will adopt some

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Speaker 2: of those approaches and some of that technology, but fundamentally,

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Speaker 2: how is it going to change the economics the tokenomics

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Speaker 2: of the AI world. That's the big question. And surely

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Speaker 2: it's got to push down prices over time.

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Speaker 1: Well you'd think so. But on the other hand, Sam

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Speaker 1: Altman said that you know that even at two hundred

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Speaker 1: dollars a month, they're not making any money from a

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Speaker 1: single user based on usage. So whether or not I

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Speaker 1: can push it down enough for the like of open

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Speaker 1: ai to reclaim the what close to coming up to

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Speaker 1: trillion dollars or whatever, it is that they're they're planning

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Speaker 1: on spending on developing their models. It seems difficult to envisage.

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Speaker 1: I truly really do see open ai and as more

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Speaker 1: of a research institution that's being funded by private capital.

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Speaker 1: I do think that anybody who is expecting to get

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Speaker 1: a return on investment might be shocked down the line

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Speaker 1: when it comes to open ai specifically. Although it's got

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Speaker 1: the backing of Microsoft, you know, it's got all that

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Speaker 1: Microsoft money in it, so maybe it will just get

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Speaker 1: folded into there at some point and some of those

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Speaker 1: investors will see a little bit of return, but yeah,

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Speaker 1: it's just a huge amount invested for what that has

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Speaker 1: been produced. If they are still struggling to make any

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Speaker 1: money at two hundred dollars an hour, as two hundred

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Speaker 1: dollars a month.

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Speaker 2: So yeah, and that's for that pro chat GPTs pro

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Speaker 2: for basically enterprise licenses two hundred US a month. And

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Speaker 2: that plan allows you access at the moment to open

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Speaker 2: ayes new agent, which is called Operator. It's just been

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Speaker 2: put out sort of as a beta release, and so

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Speaker 2: you know, this really I think is the is the

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Speaker 2: beginning of trying to accelerate development to try and claw

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Speaker 2: back some of that money and be able to charge

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Speaker 2: more of this. We've talked about agents before, where you

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Speaker 2: get this AI on your behalf to undertake tasks. So

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Speaker 2: Operator we'll look at a web browser, will look at

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Speaker 2: what is going on in that web browser, and potentially

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Speaker 2: just by looking at it, rather than needing an API

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Speaker 2: or anything like that, it can read what's on the

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Speaker 2: screen and it will suggest things and make decisions on that.

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Speaker 2: So they're working with a bunch of sort of big

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Speaker 2: US companies to test that out there, likes Uber and

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Speaker 2: those sorts of companies, so trying to do day to

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Speaker 2: day mundane tasks and automate them. So Operator is really

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Speaker 2: their big push. We've talked about Salesforce and others Microsoft

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Speaker 2: who are rolling up agents, so we've yet to see

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Speaker 2: what the cost implications of that. And of course they

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Speaker 2: launched last week chat gpt gov as well, so a

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Speaker 2: lot of American government bureaucrats have been using chat GPT.

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Speaker 2: They'd probably be less of them soon with the DOGE initiative,

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Speaker 2: but they're well into it. Ninety thousand of them have

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Speaker 2: been experimenting with it. So chat GPT Gov is basically

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Speaker 2: chat GPT, but in a secure environment in the Azure

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Speaker 2: cloud and all of those policies and that that federal

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Speaker 2: workers need to adhere to. I sort of built into

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Speaker 2: it in terms of how you access and share and

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Speaker 2: use information, so that I think that the answer for

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Speaker 2: open AI to competitors like deepseek is that they're a

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Speaker 2: big trusted American company. They need to forge your head

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Speaker 2: now with monetizing their large language models in ways that

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Speaker 2: are going to see big companies and governments and consumers

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Speaker 2: using their agents and their AI assistance.

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Speaker 1: Yeah, I going back to operator, I have to say

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Speaker 1: I don't quite get it, and like I kind of

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Speaker 1: understand that it's a cool idea for a robot that

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Speaker 1: can navigate a website, right, Like that's kind of interesting theoretically,

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Speaker 1: but it's always going to be significantly worse than apish

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Speaker 1: And if you have, like if I would rather have

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Speaker 1: a chat GPT integration with Uber API or like door

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Speaker 1: Dash API or whatever else, if we can figure out

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Speaker 1: a way to improve that system, make that more accessible,

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Speaker 1: because these are websites designed for human navigation and for

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Speaker 1: human eyes and human brains, and I think maybe as

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Speaker 1: a test of being able to emulate a human like capability,

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Speaker 1: it's a good experiment, but you know, looking at some

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Speaker 1: of the reporting around the use of operator, it's been okay,

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Speaker 1: it can do some things. It needs some intervention to

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Speaker 1: help it along, but for the most part it be

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Speaker 1: more efficient just to do it yourself from the start.

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Speaker 1: Whether that can ever become better than that, whether it

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Speaker 1: can reach the point where it's fully useful, is a

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Speaker 1: big question mark for me, because especially when you've got

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Speaker 1: the possibility of creating something that is native to computers

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Speaker 1: to be able to integrate with. So yeah, as an

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Speaker 1: interesting one, cool, but I'm not sure of the impact

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Speaker 1: that it's going to actually have in the long term.

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Speaker 2: We'll see it's powered by a computer using agent model,

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Speaker 2: which basically uses the buttons, the navigation menus, the forms

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Speaker 2: on a web page, and I guess part of the

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Speaker 2: reason why they're doing that is if you want to

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Speaker 2: interact with several different services, I don't know how it

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Speaker 2: works to have several APIs maybe operating at the same time.

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Speaker 2: So maybe there's some limitations that they're trying to overcome there.

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Speaker 2: But the sorts of companies that they're working with Door Dash, eBay, Instacart,

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Speaker 2: price Line, stub Hub, I think it will be pretty

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Speaker 2: simplistic sort of stuff. You know, do you want to

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Speaker 2: buy something on eBay? Do you want to search for

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Speaker 2: tickets on stub Hub? Can you get an AI agent

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Speaker 2: to do this? And look, I don't have huge expectations

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Speaker 2: for agents in maybe on the likes the Salesforce platform,

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Speaker 2: where they're controlling the whole platform, they've got access to

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Speaker 2: all of your data. It's probably a bit easier to do.

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Speaker 2: But this sort of stuff where you roam across the

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Speaker 2: web is going to take a lot longer to get right.

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Speaker 1: Yeah, but maybe maybe I'm just being a luddyite, you know,

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Speaker 1: maybe I'm just not Maybe I'm not the visionary, the

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Speaker 1: Silicon Valley person who can see the future.

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Speaker 2: Yeah, i'd see the demos hopefully in the next few months.

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Speaker 2: Some people do innovative things with it. But meanwhile, back

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Speaker 2: here in New Zealand, I mean, it's it's been really good.

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Speaker 2: I've seen some really thoughtful commentary on deep seek from

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Speaker 2: AI community here and startups and that. But looking at governments,

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Speaker 2: some developments being last week to give public servants a

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Speaker 2: bit more guidance on how to use AI. This is

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Speaker 2: the framework which we thought was going to sort of

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Speaker 2: come out last September, so quite a big delay on that.

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Speaker 2: Do you make of it? This plan on a page.

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Speaker 1: Yeah, it's pretty basic, isn't it. I Mean it's a

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Speaker 1: busy page, but kind of really just comes down to

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Speaker 1: figure out where it might be useful and then use

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Speaker 1: it like that seems to be the kind of the

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Speaker 1: kind of distillation excuse the term of what they've got

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Speaker 1: on the page there. I think more interesting is kind

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Speaker 1: of the responsible guidance that they there's a responsible use

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Speaker 1: guidance that they released. I think that kind of might

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Speaker 1: help people to think through that that thing of well,

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Speaker 1: where I'm using it, is it going to be useful?

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Speaker 1: And how am I going to use it? It gives quite

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Speaker 1: a good range of kind of guidelines for public service

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Speaker 1: about what are the appropriate ways to use it, what

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Speaker 1: to be cautious of, how it can be useful. And

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Speaker 1: I talked to Freth Tweety from Simply Privacy, who's been

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Speaker 1: a guest before, and she said that it avoided using

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Speaker 1: risk language, which is her way of saying, you know,

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Speaker 1: it's more like gentle kind of gentle boundaries for the

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Speaker 1: users of the public service. So overall, I think that

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Speaker 1: guidance is probably a bit more interesting and useful to

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Speaker 1: look at if you want to understand how the public

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Speaker 1: service is planning to use it, whereas that one pager

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Speaker 1: is kind of like, oh, yeah, we're going to use

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Speaker 1: it all over the place and it's going to be great.

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Speaker 2: Yeah, lots of AI buzzwords. There's lots of you know,

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Speaker 2: the OECDS principles and responsible use of AI, inclusive growth,

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Speaker 2: human rights, transparency, accountability, all of that sort of stuff,

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Speaker 2: which is great, you know, before we race off and

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Speaker 2: use this. But I think, as people like Frith have

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Speaker 2: pointed out, there's really not much detail about, you know,

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Speaker 2: how you implement this and the capability, what is being

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Speaker 2: done to build the capability. And that is a real

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Speaker 2: problem because a survey by DA of government departments last

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Speaker 2: year they asked them what is the big barrier to

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Speaker 2: the uptake off AI, and they said skills and capability.

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Speaker 2: That was by far that the big barrier. We just

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Speaker 2: don't have enough people, particularly with what is going on

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Speaker 2: with the restructuring off the public service. They're not really

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Speaker 2: empowered to spend time thinking about this. So this is

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Speaker 2: all well and good to have a framework and to

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Speaker 2: be referring to that as you develop AI. But we've

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Speaker 2: got to get going, we've got to start building stuff,

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Speaker 2: and at the moment it just seems like a massive

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Speaker 2: lull because of the disruption, the lack of funding. So

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Speaker 2: what is the plan to actually get a workforce in

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Speaker 2: the public sector, you know, sandboxing things, experimenting, sharing ideas,

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Speaker 2: launching things. That's what Judith Collins, as Digitizing Government Minister

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Speaker 2: wants two years on from chat GPT's debut, really not

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Speaker 2: seeing anything substantive other than what Callahan Innovation did with

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Speaker 2: its rather small experiment gove GPT and that team. What's

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Speaker 2: the future of them once Callahan's disestablished.

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Speaker 1: Yeah, yeah, And I think it kind of speaks a

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Speaker 1: little bit to the fact that it does take more

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Speaker 1: time then maybe Judith Collins might have expected to actually

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Speaker 1: get these projects going and figure out where it is

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Speaker 1: effective and time saving and products of it enhancing and

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Speaker 1: where it's just doing the same doing a similar thing

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Speaker 1: at the similar pace. And that's probably a general issue

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Speaker 1: across the technology, is that there's a lot of use it.

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Speaker 1: It will enhance productivity. Just get in there, get in

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Speaker 1: there and use it and use it, and it's like, well, Okay,

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Speaker 1: that's a good first step, but then that experimentation needs

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Speaker 1: to be a little bit more focused to say, here's

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Speaker 1: an idea of what I can do. Let's test it

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Speaker 1: to see if it works, and let's look at the output,

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Speaker 1: let's assess it.

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Speaker 2: Let's look at.

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Speaker 1: How long that actually takes from beginning to end versus

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Speaker 1: a human doing it and balancing all of these things

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Speaker 1: and then putting them into production workflows. Actually a little

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Speaker 1: bit more difficult, not impossible, but it does take dedicated

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Speaker 1: time and effort and planning and thought.

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Speaker 2: Yeah, oh well, at least they've got the they've laid

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Speaker 2: the groundwork now, so everyone should hopefully be on the

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Speaker 2: same PowerPoint slide.

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Speaker 1: Well there's only one so now, christ Church Company lumin

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Speaker 1: Like many New Zealand startups, it grew out of a

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Speaker 1: frustrating problem.

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Speaker 2: Yeah, think back over ten to fifteen years before cloud

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Speaker 2: platforms became entrenched about what a pain in the BUTTT

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Speaker 2: was editing and sharing collaborating on documents.

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Speaker 1: Adobe ranged supreme with its Adobe Acrobat software and the

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Speaker 1: PDF format.

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Speaker 2: Great concept of universal file format you could open anywhere,

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Speaker 2: but Adobe wanted to charge you a fair chunk of

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Speaker 2: cash to use it, and the free PDF reader really

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Speaker 2: wasn't that great.

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Speaker 1: So into Max Ferguson, who had studied civil engineering at

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Speaker 1: both Canterbury University and Stanford before getting into computer science

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Speaker 1: and software, and he's seen the nightmare of swapping documents

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Speaker 1: in the construction industry where files were edited and emailed

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Speaker 1: around or swapped on USB sticks, which was pretty much

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Speaker 1: the norm everywhere at the time.

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Speaker 2: So he set out to change that and rode the

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Speaker 2: SaaS wave to global success.

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Speaker 1: And so, Peter, you sat down with Max Ferguson from

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Speaker 1: Lumen to have a discussion about the company, its history

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Speaker 1: and where it's headed. So let's have a listen to

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Speaker 1: that interview now.

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Speaker 2: Max, Welcome to the business of tech. Congratulations one hundred

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Speaker 2: million customers for LUMAN, New Zealand founded software company. That

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Speaker 2: is staggering. You know, I'm trying to think of companies

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Speaker 2: founded in New Zealand that have that sort of level

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Speaker 2: of reach. I mean, zero has something like four point

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Speaker 2: two million customers, have done incredibly well. Can you think

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Speaker 2: of any other software company that has that sort of

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Speaker 2: usage around the world founded in New Zealand?

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Speaker 3: Not too many, Peter, thanks for having me, but yeah,

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Speaker 3: not too many. It is quite a large scale achievement

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Speaker 3: for Lumen, and you know, we're all about scale, but

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Speaker 3: I can't think of it too many others that have

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Speaker 3: sort of reached that scale coming out of New Zealand.

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Speaker 2: So break that down for US one hundred million customers.

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Speaker 2: I'm a big Google Workspace user, so I've used Lumen

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Speaker 2: as a free user because it's just rarely that I

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Speaker 2: need to edit a PDF. But this is a bit

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Speaker 2: of software that sits on in ecosystems like Google Workspace.

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Speaker 2: I had to look at You've had something like twenty

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Speaker 2: three million downloads off Lumen in the cloud pdf environment,

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Speaker 2: So I guess it's not really a download. It plugs

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Speaker 2: into your Google Workspace so you can edit pdf sign documents.

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Speaker 2: And where is the rest of your user base coming from?

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Speaker 3: Yeah, So we you know, at Lumin, we're really big

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Speaker 3: on integrations. We set out to solve the problem of

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Speaker 3: allowing people to work with PDF files more easily, so

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Speaker 3: merge files, signed pdf files. A lot of people are

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Speaker 3: kind of filling out forms, and we integrate with a

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Speaker 3: lot of the major players, so with Google Workspace as

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Speaker 3: you mentioned better, and we integrate with Microsoft Office three six,

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Speaker 3: five and we're announcing integration with Salesforce leaders. Yeah, so

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Speaker 3: it's really us integrating with those other platforms and then

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Speaker 3: allowing our users to kind of work with pedif files

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Speaker 3: and get documents signed.

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Speaker 2: So presumably then would the majority of your customers be

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Speaker 2: working sort of in the Microsoft three six five Windows environment.

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Speaker 3: A lot of our customers are using Windows, but a

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Speaker 3: lot of them are just accessing Lumen as a cloud service.

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Speaker 3: So they'll just type into Google search, you know, emerged

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Speaker 3: pdf files or search for Lumen and they'll use our

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Speaker 3: service directly at luminpdf dot com and they can upload

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Speaker 3: documents to that and get them signed or for platforms,

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Speaker 3: whatever they're looking to do on the day.

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Speaker 2: In the Google world, you're definitely one of the big

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Speaker 2: plays here. There's another one called doc Hub. I'm sure

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Speaker 2: you know well has had something like fifty eight million downloads,

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Speaker 2: but there's this sort of cluster of companies that are

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Speaker 2: allowing you to do smart things with PDF. And after

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Speaker 2: that you go down to small Pdf, which is four

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Speaker 2: million downloads. So you and dock hub are definitely in

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Speaker 2: that ecosystem anyway, the big ones, this all sort of

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Speaker 2: congregates around the PDF software. Adobe Acrobat, which created that format.

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Speaker 2: It's been around for decades. But there's clearly obviously a

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Speaker 2: lot of reasons why people don't just want to use

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Speaker 2: Adobe Acrobat, which incidentally in the Google workspace and the

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Speaker 2: Google Cloud has almost exactly the same number of downloads

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Speaker 2: as Luhman has. So why are people not just using

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Speaker 2: the industry default, the creator that came up with this

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Speaker 2: piece of software, But it's going to all these alternatives,

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Speaker 2: particularly lumen.

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Speaker 3: So what we do at Luhman pdf is a part

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Speaker 3: of it, but it is just a small part of

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Speaker 3: what we do. We like to help customers with all

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Speaker 3: of their workflows, so we like to drive efficiency and

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Speaker 3: a lot of that is, you know, signing workflows. So

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Speaker 3: here in New Zealand, we work with Renti, which is

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Speaker 3: a property management company and we actually handle about a

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Speaker 3: good portion of all of the rental agreements that are

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Speaker 3: signed in New Zealand. So Luhmann does a lot more

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Speaker 3: than just the PDF editing part. Of course, we're very

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Speaker 3: proud of our PDF editor and it gets a huge

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Speaker 3: amount of usage from people that are looking to highlight documents,

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Speaker 3: signed documents and share them. But it is just a

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Speaker 3: small part of kind of what Luman does. Luman helps

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Speaker 3: customers from all different aspects, all different verticals with their

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Speaker 3: kind of document workflow jobs.

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Speaker 2: And what does it involve when you're working with pdf S,

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Speaker 2: which is a sort of a format that came out

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Speaker 2: of Adobe, do you have to license that technology from them?

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Speaker 3: No, So a few years ago, I think it was

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Speaker 3: two thousand and six, Adobe actually open sourced the PDF standard.

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Speaker 3: And I don't know exactly they're thinking from, you know,

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Speaker 3: from it, but my understanding was was they really wanted

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Speaker 3: to build an ecosystem around that. So they had the

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Speaker 3: option to sort of keep Adobe PDFs as a closed

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Speaker 3: sort of closed a walled garden. But then you know

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Speaker 3: that that wouldn't allow the ecosystem to flourish, So that

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Speaker 3: wouldn't allow new products to come into the market, and

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Speaker 3: it would probably start to hander widespread adoption of the format.

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Speaker 3: And so Adobe decided to open source that format and

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Speaker 3: allow other players to come into the market and offer

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Speaker 3: services around that. For Adobe, the PDF part of their

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Speaker 3: business is actually a small you know, it's still significant,

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Speaker 3: but it is a small part of their business. They

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Speaker 3: offer a whole lot of other products, specifically around their

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Speaker 3: creative cloud or their document management and so by open

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Speaker 3: sourcing that they were you know, they allowed other products

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Speaker 3: to come into the market and kind of help build

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Speaker 3: out an ecosystem of tools which work around the PDF

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Speaker 3: far format.

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Speaker 2: LUMANN was founded in twenty fourteen. Back around that time,

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Speaker 2: you were a civil engineering student at the University of Canterbury,

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Speaker 2: so very much going on that track into building things

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Speaker 2: infrastructure and alike in New Zealand. But what was it

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Speaker 2: then when you were studying at UNIVERSE that made you

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Speaker 2: think there's an opportunity here and I want to go

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Speaker 2: into entrepreneurial endeavor around software.

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Speaker 3: I was quite interested in software from you know, early

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Speaker 3: days when I was in high school. I wrote a

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Speaker 3: few games on a calculator and kind of I was

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Speaker 3: just there was my first foray into learning a bit

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Speaker 3: about software. I then studied Civil engineering at UC where

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Speaker 3: I got I was able to take a whole bunch

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Speaker 3: of software courses and learn about programming and learn about software.

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Speaker 3: But I think the real entrepreneurial part didn't get started

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Speaker 3: until I left and went into the industry and realized

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Speaker 3: that some of the tools we were using in the

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Speaker 3: industry needed to be updated. There was a real opportunity

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Speaker 3: for innovation there and for me that you know, that

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Speaker 3: came around kind of managing files and just seeing how

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Speaker 3: that was done. So at the time we had you know,

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Speaker 3: I was working in construction. We had a side office

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Speaker 3: and we'd print out documents and kind of draw on

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Speaker 3: They were plans for bridges and that sort of thing.

436
00:26:00,280 --> 00:26:02,399
Speaker 3: So we draw the changes and then we would need

437
00:26:02,440 --> 00:26:05,040
Speaker 3: to get those back to the design engineers that that

438
00:26:05,119 --> 00:26:07,919
Speaker 3: kind of came up with those designs, and so we

439
00:26:08,240 --> 00:26:10,280
Speaker 3: either needed to take photos with our phone or we

440
00:26:10,320 --> 00:26:12,399
Speaker 3: could sort of scan those back in and email them.

441
00:26:13,600 --> 00:26:16,760
Speaker 3: But as you can imagine, very quickly it became quite messy.

442
00:26:16,840 --> 00:26:19,439
Speaker 3: So we had all these different plans with kind of

443
00:26:19,520 --> 00:26:23,159
Speaker 3: hand drawn you know, annotations and markups on them, and

444
00:26:23,760 --> 00:26:27,879
Speaker 3: you know, multiple versions, so it became quite complex, and

445
00:26:27,960 --> 00:26:31,240
Speaker 3: so that inspired me to create Leman, where you know,

446
00:26:31,280 --> 00:26:34,040
Speaker 3: everything was done in the cloud and you could just

447
00:26:34,119 --> 00:26:37,840
Speaker 3: have a single file where people were working on it collaboratively,

448
00:26:38,600 --> 00:26:41,760
Speaker 3: so single PF document and each person could be making

449
00:26:41,800 --> 00:26:45,480
Speaker 3: those annotations in real time and you wouldn't need to

450
00:26:45,520 --> 00:26:48,680
Speaker 3: sort of email around different versions or anything like that.

451
00:26:49,960 --> 00:26:52,919
Speaker 3: So it was a time where you Google Drive and

452
00:26:53,000 --> 00:26:56,399
Speaker 3: drop Box were really helping like starting to solve that

453
00:26:56,440 --> 00:27:00,000
Speaker 3: problem as well. And so by integrating with those platforms,

454
00:27:00,240 --> 00:27:02,720
Speaker 3: we were able to build something out which allowed people

455
00:27:02,720 --> 00:27:04,760
Speaker 3: to sort of all get on the same page quite quickly.

456
00:27:05,520 --> 00:27:08,240
Speaker 2: Yeah, and you sort of resisted the temptation to just

457
00:27:08,320 --> 00:27:12,800
Speaker 2: build a sort of a BIM system building information management system,

458
00:27:12,840 --> 00:27:15,760
Speaker 2: which would have employed all of the knowledge you had

459
00:27:15,760 --> 00:27:19,000
Speaker 2: about the construction sector, and that would which would have

460
00:27:19,000 --> 00:27:21,439
Speaker 2: been quite a niche product. And there's been a lot

461
00:27:21,440 --> 00:27:23,639
Speaker 2: of innovation since in the last decade in that space.

462
00:27:23,640 --> 00:27:26,080
Speaker 2: But you decided to go big. Everyone is having this

463
00:27:26,200 --> 00:27:30,480
Speaker 2: problem about keeping on the same page literally with one document,

464
00:27:31,400 --> 00:27:35,160
Speaker 2: but you know that that was probably quite daunting. It's

465
00:27:35,200 --> 00:27:38,960
Speaker 2: like you're in christ Church, you know, tiny development house.

466
00:27:40,000 --> 00:27:43,520
Speaker 2: How do you even think about getting this thing global

467
00:27:43,560 --> 00:27:44,919
Speaker 2: exposure at that point?

468
00:27:45,760 --> 00:27:50,240
Speaker 3: Yeah, definitely for us, Like for me at least, you know,

469
00:27:50,320 --> 00:27:55,240
Speaker 3: scale is always very important in building software. So software

470
00:27:55,280 --> 00:27:57,679
Speaker 3: works on this beautiful economy of scale where if you

471
00:27:57,680 --> 00:28:00,320
Speaker 3: can build something that has a huge impact for a

472
00:28:00,320 --> 00:28:03,720
Speaker 3: lot of people, then you can find a business model

473
00:28:03,760 --> 00:28:08,159
Speaker 3: and develop that software more. So, you know, from for me,

474
00:28:08,400 --> 00:28:11,920
Speaker 3: scale was really important from day one, and I think

475
00:28:11,920 --> 00:28:15,760
Speaker 3: as kiwis as well, we're sort of we're we have

476
00:28:15,840 --> 00:28:18,320
Speaker 3: to think that way because if you build a piece

477
00:28:18,320 --> 00:28:20,640
Speaker 3: of software like a PDF editor that's you know, only

478
00:28:20,680 --> 00:28:23,040
Speaker 3: for New Zealand, there's just not going to be enough

479
00:28:23,040 --> 00:28:25,480
Speaker 3: scale and enough usage here to develop that into a

480
00:28:25,520 --> 00:28:29,320
Speaker 3: real world leading product. So for me, you know, I

481
00:28:29,359 --> 00:28:31,320
Speaker 3: was really interested in how do we how do we

482
00:28:31,359 --> 00:28:33,679
Speaker 3: scale this thing, how do we kind of get this

483
00:28:33,760 --> 00:28:38,440
Speaker 3: thing growing really really quickly? And that's where the old

484
00:28:38,480 --> 00:28:40,760
Speaker 3: saying around you know, standing on the shoulders of giants

485
00:28:40,840 --> 00:28:45,520
Speaker 3: comes in. So we got really into integrations from day one.

486
00:28:45,600 --> 00:28:48,000
Speaker 3: So we integrated, you know, the first version of Lemon

487
00:28:48,440 --> 00:28:52,480
Speaker 3: integrated with Dropbox, Google Drive, and one Drive I think

488
00:28:52,480 --> 00:28:56,440
Speaker 3: it was SkyDrive at the time from day one, and

489
00:28:56,480 --> 00:28:58,880
Speaker 3: that allowed us to extend those platforms and reach a

490
00:28:58,920 --> 00:29:03,520
Speaker 3: lot of people there really quickly. And we've continued that

491
00:29:03,720 --> 00:29:06,880
Speaker 3: kind of philosophy right through with Lomans. So whenever we're

492
00:29:06,880 --> 00:29:10,120
Speaker 3: building new products, we're trying to build things that will

493
00:29:10,160 --> 00:29:13,560
Speaker 3: have an impact on a huge amount of people. And

494
00:29:13,600 --> 00:29:17,840
Speaker 3: we're also working really closely with partners, so we're figuring

495
00:29:17,840 --> 00:29:20,760
Speaker 3: out where we can integrate and add functionality to other

496
00:29:20,760 --> 00:29:21,880
Speaker 3: people's platforms.

497
00:29:22,720 --> 00:29:27,160
Speaker 2: So you're in these ecosystems now drop Box, Google Drive, OneDrive,

498
00:29:27,240 --> 00:29:31,000
Speaker 2: SkyDrive back then it's fine. It's a bit like being

499
00:29:31,000 --> 00:29:33,520
Speaker 2: in the app store, but there's two million other apps.

500
00:29:33,560 --> 00:29:36,600
Speaker 2: So how do you actually then get customers to decide

501
00:29:36,600 --> 00:29:40,680
Speaker 2: to choose lumin pdf over some of the alternatives.

502
00:29:41,440 --> 00:29:46,120
Speaker 3: Yeah, we're incredibly product focused for us, so you know,

503
00:29:46,320 --> 00:29:48,680
Speaker 3: all of them from day one. All of the profits

504
00:29:48,720 --> 00:29:51,360
Speaker 3: we made from the company, we hoard as much of

505
00:29:51,360 --> 00:29:54,920
Speaker 3: that as we could back into product development. You see

506
00:29:54,960 --> 00:29:57,240
Speaker 3: a model now with a lot of software where you know,

507
00:29:57,280 --> 00:29:59,320
Speaker 3: they build the software for a year or two, they

508
00:29:59,360 --> 00:30:02,280
Speaker 3: put it up there and then never updated again. We're

509
00:30:02,400 --> 00:30:04,440
Speaker 3: you know, we think it's always evolving, and we're always

510
00:30:04,480 --> 00:30:10,480
Speaker 3: looking for ways to improve the platform. Things like the

511
00:30:10,520 --> 00:30:13,720
Speaker 3: auto sync so when someone you know, when we've got

512
00:30:13,920 --> 00:30:17,440
Speaker 3: multiple people editing a PDF and all of them are

513
00:30:17,440 --> 00:30:20,320
Speaker 3: sort of drawing at once. That took us years to

514
00:30:20,360 --> 00:30:23,640
Speaker 3: get that really really refined so that it would keep

515
00:30:23,680 --> 00:30:27,360
Speaker 3: everyone's annotations so they could all see them in real time,

516
00:30:27,640 --> 00:30:29,640
Speaker 3: and then so that we could also save the copies

517
00:30:29,720 --> 00:30:32,240
Speaker 3: back to Google Drive or drop Box or one drive

518
00:30:32,600 --> 00:30:36,280
Speaker 3: without any errors. That's the sort of technology that takes

519
00:30:36,600 --> 00:30:40,200
Speaker 3: years to really develop and refine, so we kind of

520
00:30:40,200 --> 00:30:44,040
Speaker 3: continue to invest in product and building the best product

521
00:30:44,080 --> 00:30:44,760
Speaker 3: for our customers.

522
00:30:45,360 --> 00:30:48,120
Speaker 2: And then, of course, the great thing about these ecosystems

523
00:30:48,160 --> 00:30:52,080
Speaker 2: is the transparency of what the user thinks of them.

524
00:30:52,160 --> 00:30:55,000
Speaker 2: So there's star ratings. For instance, I think you have

525
00:30:55,040 --> 00:30:58,959
Speaker 2: three point seven star rating on Google Workspace. So how

526
00:30:59,000 --> 00:31:04,040
Speaker 2: important was those those reviews that feedback from this growing

527
00:31:04,200 --> 00:31:08,640
Speaker 2: customer base. How important was that to actually showing people

528
00:31:08,680 --> 00:31:10,600
Speaker 2: this is the best one or one of the better ones.

529
00:31:10,640 --> 00:31:13,520
Speaker 2: I need to maybe download this one.

530
00:31:13,800 --> 00:31:18,520
Speaker 3: Yeah, I think it's incredibly important. We read every review

531
00:31:18,560 --> 00:31:21,320
Speaker 3: that gets posted on every platform. So whether it's you know,

532
00:31:21,440 --> 00:31:25,760
Speaker 3: G two, Google Workspace, you name it, whatever platform, we've

533
00:31:25,760 --> 00:31:29,160
Speaker 3: got our product owners reading every single review. And that

534
00:31:29,280 --> 00:31:33,440
Speaker 3: means that if our customers give us feedback, like you know,

535
00:31:33,560 --> 00:31:36,000
Speaker 3: the load time was too slow or something like that,

536
00:31:36,640 --> 00:31:39,080
Speaker 3: then we'll be working on that and to fix it.

537
00:31:39,800 --> 00:31:42,920
Speaker 3: And the amazing thing about reaching that one hundred million

538
00:31:43,040 --> 00:31:46,000
Speaker 3: user milestone is that we get a lot of feedback

539
00:31:46,520 --> 00:31:48,720
Speaker 3: and we love we love feedback. We need more of it,

540
00:31:48,800 --> 00:31:52,440
Speaker 3: but we use that to make the platform better. So

541
00:31:52,600 --> 00:31:55,840
Speaker 3: maybe you know, you might have a really niche use

542
00:31:55,880 --> 00:31:59,600
Speaker 3: case for for PDF editing for example, you know, you

543
00:31:59,680 --> 00:32:02,880
Speaker 3: may be really big on you know, using our green

544
00:32:02,960 --> 00:32:07,480
Speaker 3: highlighter or something like that. If you find something wrong

545
00:32:07,480 --> 00:32:09,720
Speaker 3: with it and you give us feedback and then we

546
00:32:09,760 --> 00:32:12,000
Speaker 3: can go and fix that. And because we've got that

547
00:32:12,080 --> 00:32:15,040
Speaker 3: scale of one hundred million users, it means that all

548
00:32:15,080 --> 00:32:18,680
Speaker 3: of those niche use cases, however niche they are, will

549
00:32:18,720 --> 00:32:20,920
Speaker 3: get covered and we can build the product and make

550
00:32:20,920 --> 00:32:23,320
Speaker 3: it as good as it possibly can for our end users.

551
00:32:23,560 --> 00:32:26,320
Speaker 2: Like a lot of sort of software as a service offerings,

552
00:32:26,320 --> 00:32:29,200
Speaker 2: it's a sort of a there's a freemium model there,

553
00:32:29,240 --> 00:32:31,680
Speaker 2: so you can get the free one on Google. That's

554
00:32:31,760 --> 00:32:35,520
Speaker 2: three documents you can edit per month, which for a

555
00:32:35,520 --> 00:32:37,480
Speaker 2: business is not really going to cut it fine for

556
00:32:37,560 --> 00:32:41,400
Speaker 2: me as an individual. What's your experience been like watching

557
00:32:41,520 --> 00:32:44,160
Speaker 2: customers go from maybe testing out the free one to

558
00:32:44,240 --> 00:32:47,520
Speaker 2: then going to the nine dollars US plan and maybe

559
00:32:47,520 --> 00:32:50,280
Speaker 2: even you know, the more sort of premium when I

560
00:32:50,280 --> 00:32:52,120
Speaker 2: think one hundred and ninety nine dollars is the top

561
00:32:52,200 --> 00:32:55,520
Speaker 2: end business plan. What's been the key to sort of

562
00:32:55,600 --> 00:32:58,840
Speaker 2: getting people comfortable with the product and then sort of

563
00:32:58,920 --> 00:33:01,400
Speaker 2: upselling them to become regular paying customers.

564
00:33:01,520 --> 00:33:05,920
Speaker 3: Yeah, there's so we love it. We love that model,

565
00:33:06,240 --> 00:33:08,720
Speaker 3: and the reason why is I think we've we've probably

566
00:33:08,720 --> 00:33:10,720
Speaker 3: all been in this situation where we've gone out and

567
00:33:10,760 --> 00:33:13,200
Speaker 3: bought something and then we found that it wasn't quite

568
00:33:13,280 --> 00:33:15,600
Speaker 3: what it was hyped up to be. So, whether that's

569
00:33:15,600 --> 00:33:18,000
Speaker 3: a physical product like an ice cream, or whether that's

570
00:33:18,000 --> 00:33:19,960
Speaker 3: a digital product where you had to buy it ahead

571
00:33:19,960 --> 00:33:22,640
Speaker 3: of time or using it and then you kind of

572
00:33:22,640 --> 00:33:24,960
Speaker 3: get that disappointment of, oh, wow, this is not as

573
00:33:25,640 --> 00:33:29,400
Speaker 3: great as I was expecting. So with the freemium model,

574
00:33:29,440 --> 00:33:31,640
Speaker 3: you know, we think it's fantastic because you can go in,

575
00:33:31,760 --> 00:33:33,600
Speaker 3: you can try the product, you can see if it

576
00:33:33,640 --> 00:33:36,400
Speaker 3: works for you. Like you said, Peter, you can use

577
00:33:36,440 --> 00:33:39,240
Speaker 3: it for a few documents every month and see if

578
00:33:39,240 --> 00:33:41,400
Speaker 3: you like it in the way it works, and if

579
00:33:41,440 --> 00:33:43,440
Speaker 3: it's working out really great for you, then you can

580
00:33:43,520 --> 00:33:49,080
Speaker 3: kind of upgrade and use one of our pro pro features. So,

581
00:33:49,600 --> 00:33:52,920
Speaker 3: you know, we really like that model. We think that

582
00:33:53,360 --> 00:33:55,960
Speaker 3: it allows our customers to try out our products. They

583
00:33:56,000 --> 00:33:58,800
Speaker 3: know what they're buying. There's no kind of smoke and

584
00:33:58,840 --> 00:34:01,600
Speaker 3: mirrors around, Hey, this is going to be so great,

585
00:34:01,600 --> 00:34:03,840
Speaker 3: but then when you buy it, it's not, and we

586
00:34:03,920 --> 00:34:06,880
Speaker 3: get exposure around the whole world. So lots and lots

587
00:34:06,920 --> 00:34:10,560
Speaker 3: of people try that products, so I think that that

588
00:34:10,640 --> 00:34:11,719
Speaker 3: model works really well.

589
00:34:11,800 --> 00:34:14,879
Speaker 2: That's great, and it is diversifying the sorts of things

590
00:34:14,920 --> 00:34:17,680
Speaker 2: that you're doing with lumin PDF you talked about. I

591
00:34:17,719 --> 00:34:21,920
Speaker 2: think it's called lumin sign, which is signing documents. You know,

592
00:34:21,960 --> 00:34:24,480
Speaker 2: the big player in that market is DocuSign. It's probably

593
00:34:24,520 --> 00:34:28,279
Speaker 2: got the most brand recognition. There are lots of alternatives now,

594
00:34:28,400 --> 00:34:31,840
Speaker 2: But what do you need to do technically to conform

595
00:34:31,920 --> 00:34:36,040
Speaker 2: to the standards that make a legal document a legal document?

596
00:34:36,520 --> 00:34:40,960
Speaker 2: Obviously it's one thing to technically allow someone to sign

597
00:34:40,960 --> 00:34:45,520
Speaker 2: a document that has legal standing, But is there is

598
00:34:45,560 --> 00:34:48,520
Speaker 2: there regulation underpinning that that you have to conform to.

599
00:34:48,719 --> 00:34:52,240
Speaker 3: Yeah, definitely, And unfortunately it varies in a country by country,

600
00:34:52,320 --> 00:34:56,359
Speaker 3: so every country has slightly different legislation around what it

601
00:34:56,400 --> 00:35:00,879
Speaker 3: takes to sign a document digitally. Ins we have sort

602
00:35:00,920 --> 00:35:04,000
Speaker 3: of one of the more vague pieces of law, I

603
00:35:04,000 --> 00:35:09,200
Speaker 3: would say, around signing. So for almost any document, you know,

604
00:35:09,200 --> 00:35:12,600
Speaker 3: as long as you're applying a signature to that, it's

605
00:35:12,640 --> 00:35:15,200
Speaker 3: going to be legally valid. There's a few documents that

606
00:35:15,239 --> 00:35:18,400
Speaker 3: you can't sign digitally in New Zealand, like Wells, but

607
00:35:18,480 --> 00:35:21,479
Speaker 3: we have a very vague legislation. Some of the other

608
00:35:22,200 --> 00:35:25,960
Speaker 3: countries will say that you need to you know, be

609
00:35:26,680 --> 00:35:30,040
Speaker 3: signing a document in a way that uses cryptography that

610
00:35:30,120 --> 00:35:33,480
Speaker 3: actually applies like a cryptographic signature to the document for

611
00:35:33,520 --> 00:35:34,799
Speaker 3: it to be legally bind it.

612
00:35:34,880 --> 00:35:36,600
Speaker 2: Going back a little bit, at some point, I mean

613
00:35:36,640 --> 00:35:39,000
Speaker 2: things were growing, Well, at what point did you realize

614
00:35:39,000 --> 00:35:42,040
Speaker 2: this is actually a really viable business. We're seeing one

615
00:35:42,080 --> 00:35:44,760
Speaker 2: hundreds of thousands of new customers coming on every quarter.

616
00:35:45,560 --> 00:35:47,680
Speaker 2: This is actually going to go somewhere. What point was.

617
00:35:47,640 --> 00:35:51,480
Speaker 3: That we got We got really a great initial traction

618
00:35:51,680 --> 00:35:54,920
Speaker 3: with Lumen from the start. So I've built a number

619
00:35:55,000 --> 00:35:59,360
Speaker 3: of companies and apps before Lumen, probably around ten, like

620
00:35:59,560 --> 00:36:02,840
Speaker 3: small any apps and that sort of thing, and turned

621
00:36:02,840 --> 00:36:04,600
Speaker 3: out that Lemon was the one that kind of got

622
00:36:04,600 --> 00:36:08,439
Speaker 3: the most traction the quickest. When we hit the sort

623
00:36:08,440 --> 00:36:11,839
Speaker 3: of the million user point, which was after a couple

624
00:36:11,880 --> 00:36:14,480
Speaker 3: of months, you know, I realized that there was a

625
00:36:14,520 --> 00:36:17,520
Speaker 3: real need there and there was a lot of people,

626
00:36:17,600 --> 00:36:18,959
Speaker 3: you know, I realized there was a lot of people

627
00:36:19,000 --> 00:36:22,880
Speaker 3: looking for a solution that would allow them to draw

628
00:36:23,000 --> 00:36:27,640
Speaker 3: on documents and annotate documents really easily without kind of

629
00:36:27,640 --> 00:36:30,160
Speaker 3: having to go through the email workflows and the sending

630
00:36:30,239 --> 00:36:34,000
Speaker 3: documents around or downloading. So that yea one million user

631
00:36:34,040 --> 00:36:36,439
Speaker 3: point was really really the mark for me there where

632
00:36:37,000 --> 00:36:39,240
Speaker 3: I realized that, you know, we had some good product

633
00:36:39,239 --> 00:36:39,920
Speaker 3: market fips.

634
00:36:39,760 --> 00:36:41,719
Speaker 2: And at some point along the way you did a

635
00:36:41,800 --> 00:36:44,840
Speaker 2: major overhaul of the app. What really drove that.

636
00:36:46,239 --> 00:36:49,800
Speaker 3: Yeah, So we built the app incrementally from twenty fourteen

637
00:36:49,880 --> 00:36:54,080
Speaker 3: to about twenty nineteen. We kept adding new features, and

638
00:36:54,360 --> 00:36:57,160
Speaker 3: we just you know, like we talked about earlier, we

639
00:36:57,200 --> 00:36:59,520
Speaker 3: read all of the customer reviews, and when a customer

640
00:36:59,520 --> 00:37:03,400
Speaker 3: you know, ask for certain features, we kind of added them.

641
00:37:03,480 --> 00:37:06,840
Speaker 3: But by the time we got to early twenty eighteen,

642
00:37:07,320 --> 00:37:10,440
Speaker 3: we realized that, you know, things weren't as streamlined and

643
00:37:10,480 --> 00:37:14,200
Speaker 3: as smooth as we wanted them. And at that point

644
00:37:14,239 --> 00:37:17,520
Speaker 3: we could have left the product as is, but you know,

645
00:37:17,680 --> 00:37:19,279
Speaker 3: we thought we could do more, and we thought we

646
00:37:19,320 --> 00:37:22,080
Speaker 3: could build build something better. So we actually commissioned like

647
00:37:22,120 --> 00:37:25,600
Speaker 3: a full rebuild of the app from the ground up.

648
00:37:26,480 --> 00:37:28,759
Speaker 3: We kind of got rid of like all the code

649
00:37:28,800 --> 00:37:31,480
Speaker 3: we'd written beforehand, and we just started from scratch with

650
00:37:32,120 --> 00:37:36,360
Speaker 3: new designs for the entire platform. That kicked off a

651
00:37:36,440 --> 00:37:38,960
Speaker 3: year and a half journey where we rebuilt everything that

652
00:37:39,120 --> 00:37:45,000
Speaker 3: was Lumen and then released that in twenty nineteen as

653
00:37:45,040 --> 00:37:49,359
Speaker 3: a brand new piece of software. And I can say

654
00:37:49,440 --> 00:37:51,439
Speaker 3: there was a huge amount of stress kind of leading

655
00:37:51,520 --> 00:37:54,120
Speaker 3: up to that, especially those last few weeks where you

656
00:37:54,239 --> 00:37:57,080
Speaker 3: realize you're effectively going to turn off the entire service,

657
00:37:57,120 --> 00:37:59,680
Speaker 3: which at the time had probably thirty four minion people

658
00:37:59,719 --> 00:38:03,040
Speaker 3: using it, and like cut instantly over to a new

659
00:38:03,120 --> 00:38:05,920
Speaker 3: service which had been rebuilt, which did a lot of

660
00:38:05,920 --> 00:38:08,640
Speaker 3: things better, but it also didn't do everything the old

661
00:38:08,640 --> 00:38:13,440
Speaker 3: one had done. So it was tremendously stressful. But we

662
00:38:14,120 --> 00:38:16,080
Speaker 3: got a really great outcome out of that, and the

663
00:38:16,120 --> 00:38:19,880
Speaker 3: customers loved of the new rebuilt product, and you know,

664
00:38:19,960 --> 00:38:22,560
Speaker 3: that really triggered our graft to get to where we

665
00:38:22,600 --> 00:38:23,160
Speaker 3: are now.

666
00:38:23,000 --> 00:38:26,200
Speaker 2: In just in time for the pandemic, which presumably saw

667
00:38:26,200 --> 00:38:28,400
Speaker 2: a bit of a bump in usage as well, with

668
00:38:28,440 --> 00:38:32,280
Speaker 2: people needing to exchange and work on documents remotely working

669
00:38:32,280 --> 00:38:32,719
Speaker 2: from home.

670
00:38:33,880 --> 00:38:35,520
Speaker 3: Yeah. So the way I like to think of that

671
00:38:35,680 --> 00:38:39,520
Speaker 3: is that, you know, we saw digitization for many years,

672
00:38:39,600 --> 00:38:42,400
Speaker 3: So from twenty fourteen through it to twenty twenty, we

673
00:38:42,440 --> 00:38:44,240
Speaker 3: knew a lot of people were moving to the cloud,

674
00:38:44,400 --> 00:38:46,360
Speaker 3: a lot of people were becoming familiar with you know,

675
00:38:46,440 --> 00:38:49,880
Speaker 3: tools like Google Docs and Google Drive. A lot of

676
00:38:49,920 --> 00:38:53,319
Speaker 3: businesses were moving over, but there was still some that

677
00:38:53,400 --> 00:38:56,400
Speaker 3: hadn't you know that that were based in the paper world.

678
00:38:56,960 --> 00:39:00,080
Speaker 3: And when the pandemic happened, we really saw you know

679
00:39:00,160 --> 00:39:03,520
Speaker 3: a lot of those businesses modernized really quickly. I think

680
00:39:03,520 --> 00:39:05,839
Speaker 3: they were always going to get there. It just brought that,

681
00:39:05,920 --> 00:39:08,480
Speaker 3: you know, I just should have just forced that change

682
00:39:08,480 --> 00:39:11,680
Speaker 3: to happen a lot quicker. And so there was in

683
00:39:11,800 --> 00:39:13,520
Speaker 3: the tech world there was a bit of a sort

684
00:39:13,520 --> 00:39:15,640
Speaker 3: of a boom and a bust where people thought, you know,

685
00:39:15,719 --> 00:39:19,919
Speaker 3: that growth would continue, you know of say ADOPTU signed

686
00:39:19,960 --> 00:39:23,040
Speaker 3: the stock prices went crazy, like that growth would continue forever.

687
00:39:24,200 --> 00:39:25,759
Speaker 3: I think we were a bit more measured in the

688
00:39:25,760 --> 00:39:27,520
Speaker 3: way we looked at it, and we just saw it

689
00:39:27,560 --> 00:39:30,280
Speaker 3: as a lot of businesses kind of digitizing and modernizing

690
00:39:30,360 --> 00:39:30,920
Speaker 3: quite quickly.

691
00:39:31,640 --> 00:39:35,960
Speaker 2: And at some point you also started to expand internationally

692
00:39:36,000 --> 00:39:39,400
Speaker 2: in terms of your software development. Tell us about that,

693
00:39:39,560 --> 00:39:41,840
Speaker 2: going from a small team in christ Church working on

694
00:39:42,520 --> 00:39:46,480
Speaker 2: Luhman to running teams in Southeast Asia.

695
00:39:46,520 --> 00:39:50,160
Speaker 3: Definitely. So I was always really passionate about kind of

696
00:39:50,719 --> 00:39:55,040
Speaker 3: remote work and global teams from way before the pandemic.

697
00:39:55,239 --> 00:39:58,759
Speaker 3: So if we go right back to twenty twelve, I

698
00:39:58,800 --> 00:40:01,160
Speaker 3: was quite interested in this idea that you know, multiple

699
00:40:01,200 --> 00:40:04,240
Speaker 3: people from around the world could come together. Before Luhman

700
00:40:04,400 --> 00:40:09,759
Speaker 3: even I worked with developers in India, South Africa, Ukraine, Vietnam,

701
00:40:09,920 --> 00:40:13,120
Speaker 3: Philippines and really got I got a feel for how

702
00:40:13,160 --> 00:40:15,800
Speaker 3: that might work. This was, you know, before the days

703
00:40:15,800 --> 00:40:19,080
Speaker 3: of zoom and video calls, like, it was all pretty janky,

704
00:40:19,120 --> 00:40:20,880
Speaker 3: and so there was like a lot of email going

705
00:40:20,880 --> 00:40:24,200
Speaker 3: on and maybe like some Skype and WhatsApp, but it

706
00:40:24,239 --> 00:40:27,200
Speaker 3: was I was really fascinated with you know, what happens

707
00:40:27,200 --> 00:40:29,320
Speaker 3: when a group of people from you know, different cultures

708
00:40:29,360 --> 00:40:32,920
Speaker 3: all come together to build something. And so the second

709
00:40:32,960 --> 00:40:36,759
Speaker 3: person that started working with me on Luhman, he was

710
00:40:37,000 --> 00:40:39,640
Speaker 3: a Vietnamese national living in the States. I was living

711
00:40:39,680 --> 00:40:41,839
Speaker 3: in the States at the time as well, and we

712
00:40:41,880 --> 00:40:44,600
Speaker 3: started working on this thing kind of really really early on.

713
00:40:45,920 --> 00:40:48,160
Speaker 3: He was much better on the software side than me,

714
00:40:48,280 --> 00:40:51,040
Speaker 3: so in terms of programming, you know, the guy was

715
00:40:51,040 --> 00:40:53,719
Speaker 3: was absolutely incredible and we just built this you know,

716
00:40:53,760 --> 00:40:57,920
Speaker 3: this working relationship for him and you know, his family.

717
00:40:57,960 --> 00:41:01,040
Speaker 3: At the time. He wanted to kind of moved back

718
00:41:01,080 --> 00:41:04,080
Speaker 3: to Vietnam and build out a team there. So he

719
00:41:05,120 --> 00:41:08,160
Speaker 3: left the States and moved back to Vietnam and started

720
00:41:08,160 --> 00:41:10,239
Speaker 3: building out what would end up being kind of our

721
00:41:10,320 --> 00:41:13,440
Speaker 3: Vietnamese development team. And that's how we kind of we

722
00:41:13,520 --> 00:41:16,360
Speaker 3: grew out. Since then, you know, we've we've kept a

723
00:41:16,400 --> 00:41:19,399
Speaker 3: pretty global approach on things as well, So we've got

724
00:41:19,400 --> 00:41:23,480
Speaker 3: teams and many countries all around the world working away

725
00:41:23,520 --> 00:41:25,800
Speaker 3: and we all just come together in this digital space

726
00:41:25,880 --> 00:41:27,000
Speaker 3: to build these products.

727
00:41:27,080 --> 00:41:30,200
Speaker 2: Yeah, and I think it's a model that a lot

728
00:41:30,200 --> 00:41:32,560
Speaker 2: of New Zealand companies are pursuing now. I know game

729
00:41:32,560 --> 00:41:36,200
Speaker 2: developers who have whole teams in South America because literally

730
00:41:36,280 --> 00:41:39,840
Speaker 2: getting getting the talent in New Zealand is really difficult.

731
00:41:39,880 --> 00:41:42,560
Speaker 2: We've got a small talent pool. At one point, it

732
00:41:42,600 --> 00:41:44,879
Speaker 2: was really attractive to come here. It's sort of gone

733
00:41:44,920 --> 00:41:47,799
Speaker 2: the other direction for various reasons at the moment. But

734
00:41:47,880 --> 00:41:50,240
Speaker 2: being able to reach out to a global talent pool

735
00:41:50,560 --> 00:41:52,879
Speaker 2: and not expect people to you to be coming into

736
00:41:52,880 --> 00:41:54,320
Speaker 2: the office in christ Church has got to be a

737
00:41:54,400 --> 00:41:55,040
Speaker 2: huge advantage.

738
00:41:55,160 --> 00:41:58,240
Speaker 3: Yeah, it definitely helps our team here in New Zealander

739
00:41:58,520 --> 00:42:00,560
Speaker 3: is amazing. And you know, one of the reasons I

740
00:42:00,719 --> 00:42:03,200
Speaker 3: decided to move back from the US to New Zealand

741
00:42:03,320 --> 00:42:06,440
Speaker 3: was because I thought there was a real untapped talent

742
00:42:06,520 --> 00:42:10,399
Speaker 3: poll especially down here in christ Church, got amazing people here.

743
00:42:10,920 --> 00:42:14,880
Speaker 3: What we do struggle with sometimes is finding specialists. So

744
00:42:14,960 --> 00:42:17,120
Speaker 3: if we if we need someone that's got you know,

745
00:42:17,239 --> 00:42:23,440
Speaker 3: say a very a very concentrated expertise and you know,

746
00:42:24,160 --> 00:42:27,520
Speaker 3: some bizarre part of software, then say, finding that in

747
00:42:27,600 --> 00:42:30,799
Speaker 3: New Zealand can be more challenging because we simply don't

748
00:42:30,840 --> 00:42:34,680
Speaker 3: have the population to find those specialists. And so there's

749
00:42:34,719 --> 00:42:38,040
Speaker 3: really two options then to handle those scenarios when they

750
00:42:38,040 --> 00:42:41,600
Speaker 3: come up. One is potentially bringing someone in from overseas,

751
00:42:41,840 --> 00:42:44,400
Speaker 3: so you can kind of run recruitment and then you know,

752
00:42:44,480 --> 00:42:47,160
Speaker 3: find someone overseas that might have the specialties and then

753
00:42:47,239 --> 00:42:50,360
Speaker 3: bring them into New Zealand. I know a bunch of

754
00:42:50,360 --> 00:42:52,600
Speaker 3: companies do that and it works quite well, but it

755
00:42:52,640 --> 00:42:56,640
Speaker 3: can be challenging as well because relocation then becomes part

756
00:42:56,680 --> 00:43:00,840
Speaker 3: of your your onboarding. Effectively. For us, we just like

757
00:43:00,960 --> 00:43:03,200
Speaker 3: to go out into the global market and find those

758
00:43:03,200 --> 00:43:06,360
Speaker 3: specialists where we need them and then just build a

759
00:43:06,360 --> 00:43:08,759
Speaker 3: really great relationship with them and tie them back to

760
00:43:08,840 --> 00:43:10,239
Speaker 3: our operation here in New Zealm.

761
00:43:10,320 --> 00:43:13,719
Speaker 2: One of those specialties that I'm sure you're drawing on

762
00:43:13,800 --> 00:43:16,840
Speaker 2: to a greater degree than ever is artificial intelligence. You know,

763
00:43:16,920 --> 00:43:20,560
Speaker 2: particularly with you if you if you're doing this deal

764
00:43:20,600 --> 00:43:24,320
Speaker 2: with Salesforce, you know they're all about agent force, you

765
00:43:24,360 --> 00:43:29,680
Speaker 2: know AI agents, their their AI cloud and all all

766
00:43:29,680 --> 00:43:31,600
Speaker 2: that sort of stuff. So all of that data and

767
00:43:31,640 --> 00:43:35,760
Speaker 2: whatever's done on that platform will be documented at some point.

768
00:43:35,840 --> 00:43:38,960
Speaker 2: So what's your journey being like sort of embracing particularly

769
00:43:38,960 --> 00:43:42,840
Speaker 2: this latest wave of AI, which is really around generative AI,

770
00:43:43,239 --> 00:43:45,719
Speaker 2: and how all of that is reflected in how we

771
00:43:45,760 --> 00:43:46,680
Speaker 2: work with documents.

772
00:43:46,760 --> 00:43:49,320
Speaker 3: Our approach to AI was that, you know, we wanted

773
00:43:49,360 --> 00:43:53,040
Speaker 3: to really give it some time and just see, you know,

774
00:43:53,360 --> 00:43:55,600
Speaker 3: where can we get the most value for the customer

775
00:43:56,400 --> 00:43:58,360
Speaker 3: Because I know a lot of a lot of companies

776
00:43:58,360 --> 00:44:01,279
Speaker 3: that are jumped into AI really early on, and they're

777
00:44:01,320 --> 00:44:04,560
Speaker 3: released some features that they were super cool, but we're

778
00:44:04,560 --> 00:44:08,480
Speaker 3: there actually going to help businesses grow and thrive, and

779
00:44:08,560 --> 00:44:09,880
Speaker 3: a lot of there was a lot of kind of

780
00:44:09,880 --> 00:44:13,200
Speaker 3: marketing hype around that. So what we did is we

781
00:44:13,320 --> 00:44:15,799
Speaker 3: worked away in the background for several years and tried

782
00:44:15,800 --> 00:44:18,120
Speaker 3: to figure out, you know, where can we actually deliver

783
00:44:18,560 --> 00:44:23,160
Speaker 3: huge value to our customers with this new technology. And

784
00:44:23,239 --> 00:44:25,640
Speaker 3: so we've been rolling AI into kind of a bunch

785
00:44:25,680 --> 00:44:28,399
Speaker 3: of our products over the last few years, and we've

786
00:44:28,440 --> 00:44:30,719
Speaker 3: got some huge product releases coming up this year that

787
00:44:30,800 --> 00:44:34,279
Speaker 3: will be, you know, but a fully rebuilt using the

788
00:44:34,320 --> 00:44:39,560
Speaker 3: concept of AI. My personal belief is I think that

789
00:44:39,600 --> 00:44:41,960
Speaker 3: this is this is sort of a fire or light

790
00:44:42,000 --> 00:44:46,880
Speaker 3: bulb moment for humanity. We're unlocking something here that that

791
00:44:46,920 --> 00:44:51,960
Speaker 3: has never been seen before, something incredibly powerful. So I

792
00:44:51,960 --> 00:44:55,320
Speaker 3: think it will change the software space. But there's also

793
00:44:55,360 --> 00:44:57,719
Speaker 3: a lot of kind of marketing hype and a lot

794
00:44:57,760 --> 00:45:00,839
Speaker 3: of things that are not really AI that are being

795
00:45:00,880 --> 00:45:04,280
Speaker 3: branded as AI, and so we've got to be careful

796
00:45:04,280 --> 00:45:06,160
Speaker 3: to make sure that, you know, we're actually building stuff

797
00:45:06,160 --> 00:45:09,600
Speaker 3: that's helpful for our customer that delivers tremendous value, and

798
00:45:09,640 --> 00:45:13,160
Speaker 3: we're not just going to spray painting the outside with pretty.

799
00:45:12,840 --> 00:45:16,560
Speaker 2: Colors, especially when you know some of the documents your

800
00:45:16,560 --> 00:45:20,080
Speaker 2: customers are dealing with, they're very important documents there deals

801
00:45:20,120 --> 00:45:25,840
Speaker 2: with with their own customers, their legal documents, rental agreements

802
00:45:25,880 --> 00:45:28,319
Speaker 2: and the like. So a lot of the AI might

803
00:45:28,360 --> 00:45:30,920
Speaker 2: be done in a different platform, but making sure that

804
00:45:30,920 --> 00:45:34,560
Speaker 2: that's all accurately represented, and the sort of auto generation

805
00:45:34,680 --> 00:45:37,439
Speaker 2: tools that Luman has built in as well to make

806
00:45:37,560 --> 00:45:41,600
Speaker 2: document creation and editing easier. It's got to be accurate, right,

807
00:45:41,640 --> 00:45:45,319
Speaker 2: and we do have still quality issues around hallucinations and

808
00:45:45,320 --> 00:45:49,000
Speaker 2: inaccuracies in some of these large language models, definitely.

809
00:45:48,560 --> 00:45:51,560
Speaker 3: And we're learning how to use it as people and

810
00:45:51,600 --> 00:45:54,759
Speaker 3: as business owners as well. So you know, there's there's

811
00:45:54,760 --> 00:45:57,359
Speaker 3: a lot of experimentation going on about what's safe, how

812
00:45:57,400 --> 00:46:00,760
Speaker 3: can we use this in a safe way, And businesses

813
00:46:00,760 --> 00:46:02,799
Speaker 3: are learning where they can get the most value out

814
00:46:02,840 --> 00:46:04,840
Speaker 3: of it and you know, where they should stay clear.

815
00:46:05,840 --> 00:46:08,840
Speaker 3: But we think there's you know, tremendous potential to help

816
00:46:09,320 --> 00:46:13,799
Speaker 3: eliminate some of the mundane tasks. For example, you know,

817
00:46:13,880 --> 00:46:17,920
Speaker 3: even internally at Lumen we generate employment contracts for all

818
00:46:17,920 --> 00:46:20,800
Speaker 3: of our new employees. A lot of work goes into

819
00:46:20,960 --> 00:46:24,360
Speaker 3: kind of adding people's names and addresses and double checking

820
00:46:24,400 --> 00:46:26,959
Speaker 3: and making sure all the details are right. We think

821
00:46:27,000 --> 00:46:30,600
Speaker 3: these sort of tasks are perfect for AI because AI

822
00:46:30,760 --> 00:46:33,960
Speaker 3: is really great at you know, pulling information and falling

823
00:46:34,000 --> 00:46:37,319
Speaker 3: in fields and as long as it's constrained, it's not

824
00:46:37,400 --> 00:46:41,120
Speaker 3: off totally writing its own things, then it can be

825
00:46:41,600 --> 00:46:45,360
Speaker 3: tremendously helpful. But but as you said, Peter, there is

826
00:46:45,480 --> 00:46:48,200
Speaker 3: you know, there's a lot of risks there, and I'm

827
00:46:48,200 --> 00:46:50,360
Speaker 3: sure there's going to be a few cases where you know,

828
00:46:50,400 --> 00:46:53,360
Speaker 3: hallu hallucinations cause serious problems.

829
00:46:53,440 --> 00:46:56,080
Speaker 2: So you're at one hundred million users. I think back

830
00:46:56,120 --> 00:46:58,319
Speaker 2: in twenty twenty one you had sixty millions, So the

831
00:46:58,360 --> 00:47:01,799
Speaker 2: growth is still really So what does this meant for

832
00:47:01,840 --> 00:47:07,000
Speaker 2: you sort of your capital journey? Have you basically funded

833
00:47:07,000 --> 00:47:10,040
Speaker 2: this from from from revenue? You said you put a

834
00:47:10,120 --> 00:47:12,440
Speaker 2: lot of the profits back into development. Have you had

835
00:47:12,440 --> 00:47:14,480
Speaker 2: to go out and raise money along the way.

836
00:47:14,560 --> 00:47:17,879
Speaker 3: Yeah, so we're fully bootstrapped. We've got an amazing team

837
00:47:17,920 --> 00:47:20,920
Speaker 3: of people. You know, the team at Luhmann put on

838
00:47:21,320 --> 00:47:24,520
Speaker 3: a huge amount of work to build better products and

839
00:47:25,360 --> 00:47:29,560
Speaker 3: we've managed to kind of bootstrap it right through. We're

840
00:47:29,680 --> 00:47:32,160
Speaker 3: you know, we're obviously open to taking capital. I think

841
00:47:32,160 --> 00:47:35,480
Speaker 3: there's a market out there for capital. But for us,

842
00:47:35,560 --> 00:47:38,480
Speaker 3: you know, our goals are to build amazing products and

843
00:47:38,560 --> 00:47:41,279
Speaker 3: our goals are to think long term, and so it

844
00:47:41,320 --> 00:47:44,239
Speaker 3: doesn't always align with say the you know, the VC world,

845
00:47:44,320 --> 00:47:47,400
Speaker 3: where you're trying to build something really quickly, hype it

846
00:47:47,480 --> 00:47:49,719
Speaker 3: up and then move on to the next one. It's

847
00:47:49,760 --> 00:47:51,400
Speaker 3: a little bit different from what we try to do.

848
00:47:51,480 --> 00:47:53,600
Speaker 3: We try to build you know, amazing products that really

849
00:47:53,680 --> 00:47:57,960
Speaker 3: laughs and so, you know, looking at other ways to

850
00:47:58,040 --> 00:48:00,720
Speaker 3: fundraise business. In the future we'll be will be open

851
00:48:00,800 --> 00:48:03,800
Speaker 3: to it, but for now as a bootstrip business, we

852
00:48:03,960 --> 00:48:06,200
Speaker 3: kind of love what we're doing and we think we're

853
00:48:06,280 --> 00:48:07,840
Speaker 3: having a huge impact on our customers.

854
00:48:07,880 --> 00:48:10,040
Speaker 2: Well, you've got the big three platforms, the biggest three

855
00:48:10,120 --> 00:48:12,640
Speaker 2: software platforms in the world, so you can't really go

856
00:48:12,800 --> 00:48:17,440
Speaker 2: wrong there. Just finally, Max, what would your advice be

857
00:48:17,640 --> 00:48:22,880
Speaker 2: to young software enthusiasts, budding entrepreneurs who are probably looking

858
00:48:22,920 --> 00:48:26,919
Speaker 2: at New Zealand's narrative around software, which has very much

859
00:48:26,960 --> 00:48:31,920
Speaker 2: been around business software as a service. Ven sequence, great

860
00:48:32,000 --> 00:48:35,160
Speaker 2: christ Church Company zero have done very well B to

861
00:48:35,239 --> 00:48:37,480
Speaker 2: B sort of software. This is sort of B to

862
00:48:37,560 --> 00:48:40,040
Speaker 2: B but it's really open to anyone anyone who wants

863
00:48:40,120 --> 00:48:44,640
Speaker 2: to edit documents. So in terms of not limiting your

864
00:48:44,800 --> 00:48:48,840
Speaker 2: ambition to that sort of market going, we're too small

865
00:48:48,880 --> 00:48:50,879
Speaker 2: to compete in that field. We need to go after

866
00:48:50,960 --> 00:48:54,920
Speaker 2: some tiny little niche like building information management. What is

867
00:48:54,960 --> 00:48:58,200
Speaker 2: your advice to those entrepreneurs to sort of look a

868
00:48:58,200 --> 00:49:02,560
Speaker 2: little bit more ambitiously go after that big market.

869
00:49:02,680 --> 00:49:06,640
Speaker 3: Yeah, definitely, I think for new entrepreneurs in New Zealand.

870
00:49:07,800 --> 00:49:11,040
Speaker 3: There's some really really important things. So one, thinking global

871
00:49:11,040 --> 00:49:14,480
Speaker 3: from day one is super important. Get out there and

872
00:49:14,560 --> 00:49:17,280
Speaker 3: travel if you can, and see some of the world

873
00:49:17,320 --> 00:49:20,759
Speaker 3: and understand, you know, the needs that people have in

874
00:49:20,840 --> 00:49:25,560
Speaker 3: different markets. We try to get all of our employees

875
00:49:25,600 --> 00:49:28,160
Speaker 3: at Lehman, we try to get them traveling to various

876
00:49:28,200 --> 00:49:31,160
Speaker 3: different spots around the world, be it India, be it

877
00:49:31,239 --> 00:49:35,080
Speaker 3: the United States, or Southeast Asia, to really get an

878
00:49:35,160 --> 00:49:38,399
Speaker 3: understanding of kind of all of the different markets and

879
00:49:38,400 --> 00:49:41,359
Speaker 3: and the way people think about problems. So I think,

880
00:49:41,400 --> 00:49:44,640
Speaker 3: you know, taking that global perspective from day one is

881
00:49:45,000 --> 00:49:47,360
Speaker 3: super important. The other thing I would say is just

882
00:49:47,560 --> 00:49:49,920
Speaker 3: get out there and put something in the market, try

883
00:49:50,960 --> 00:49:53,680
Speaker 3: and talk to people because there's a lot of work

884
00:49:53,719 --> 00:49:57,000
Speaker 3: to be done. There's always kind of more software to

885
00:49:57,000 --> 00:49:59,959
Speaker 3: be built or companies to be built, this huge amount

886
00:50:00,160 --> 00:50:03,239
Speaker 3: work out there to be done. So you know, just

887
00:50:03,400 --> 00:50:06,400
Speaker 3: making that first leap of faith and taking something simple,

888
00:50:06,560 --> 00:50:10,120
Speaker 3: even a really really simple prototype, and putting that out

889
00:50:10,160 --> 00:50:13,520
Speaker 3: in the market is a great way to get get started.

890
00:50:14,840 --> 00:50:16,480
Speaker 3: As we sort of talked about at the start of

891
00:50:16,520 --> 00:50:19,400
Speaker 3: this podcast, Peter Luhman was probably the tenth product I

892
00:50:19,440 --> 00:50:21,919
Speaker 3: put out in the market. It was not not necessarily

893
00:50:21,960 --> 00:50:24,160
Speaker 3: that there was no one, you know, it wasn't a

894
00:50:24,360 --> 00:50:27,480
Speaker 3: sort of a first success straight away. But for each

895
00:50:27,480 --> 00:50:29,360
Speaker 3: of those products that I put out in the market,

896
00:50:29,719 --> 00:50:33,200
Speaker 3: I learned something else. So the you know, the app

897
00:50:33,239 --> 00:50:35,440
Speaker 3: I did before Luhmann was a file converter, and it

898
00:50:35,560 --> 00:50:39,160
Speaker 3: converted files from doc X to PDF and doc X

899
00:50:39,160 --> 00:50:42,200
Speaker 3: to other formats. And I realized that through that that

900
00:50:42,239 --> 00:50:45,200
Speaker 3: file converter, I realized that, you know, PDF is a

901
00:50:45,280 --> 00:50:47,480
Speaker 3: huge part of what people do. Over seventy percent of

902
00:50:47,480 --> 00:50:49,760
Speaker 3: the files on that platform had something to do with PDF.

903
00:50:49,880 --> 00:50:52,480
Speaker 3: So you know, why not niche down into that space.

904
00:50:52,760 --> 00:50:55,160
Speaker 3: So for a yeah, a young entrepreneur would be just

905
00:50:55,320 --> 00:50:57,960
Speaker 3: think global from day one and then put things out

906
00:50:57,960 --> 00:51:01,040
Speaker 3: in the market, put messages out out on blogs, and

907
00:51:01,080 --> 00:51:02,680
Speaker 3: just see what other people think.

908
00:51:02,719 --> 00:51:05,640
Speaker 2: And so great advice, Max, I'm sure that will be

909
00:51:05,640 --> 00:51:07,719
Speaker 2: inspiring to a lot of entrepreneurs who are sort of

910
00:51:07,719 --> 00:51:10,640
Speaker 2: setting out on that same journey. How many staff you

911
00:51:10,719 --> 00:51:12,000
Speaker 2: got now, so we're.

912
00:51:11,920 --> 00:51:15,520
Speaker 3: Just over one hundred. Now we've got teams, teams all

913
00:51:15,520 --> 00:51:17,000
Speaker 3: around the world and just over one.

914
00:51:16,960 --> 00:51:20,200
Speaker 2: Hundred congratulations, one hundred million users. All the best for

915
00:51:20,520 --> 00:51:23,560
Speaker 2: hopefully the next fifty or or one hundred million users.

916
00:51:23,960 --> 00:51:25,680
Speaker 2: Thanks so much for being on the business of tech.

917
00:51:25,719 --> 00:51:27,000
Speaker 3: Thanks Peter, it's been awesome.

918
00:51:33,520 --> 00:51:36,400
Speaker 2: So Ben, what can we learn from that one hundred

919
00:51:36,440 --> 00:51:40,120
Speaker 2: million users? A lot of them probably free users. But

920
00:51:40,600 --> 00:51:43,760
Speaker 2: that premium model seems to really be working for Luhman.

921
00:51:44,200 --> 00:51:47,959
Speaker 2: It's a hundred person company, it's bootstrapped itself, it hasn't

922
00:51:48,040 --> 00:51:52,080
Speaker 2: had to take on venture capital and dilute the shareholding.

923
00:51:52,560 --> 00:51:54,480
Speaker 2: Pretty impressive model.

924
00:51:54,840 --> 00:51:57,840
Speaker 1: Yeah, and I think not to dumplay all of that

925
00:51:58,000 --> 00:52:00,400
Speaker 1: hard work, but I think they got in there early,

926
00:52:00,719 --> 00:52:03,400
Speaker 1: and they did it well, and they got those integrations

927
00:52:03,800 --> 00:52:07,560
Speaker 1: with Google Docs and you know, back in I don't

928
00:52:07,560 --> 00:52:09,839
Speaker 1: know if it's still the case, but when you went

929
00:52:09,920 --> 00:52:12,640
Speaker 1: to open a PDF in Google Drive, it would say

930
00:52:12,960 --> 00:52:14,880
Speaker 1: do you want to open it with Lumen and you

931
00:52:14,880 --> 00:52:16,840
Speaker 1: could connect to Lumin and it would give you a

932
00:52:16,840 --> 00:52:21,040
Speaker 1: little more functionality there. And then building that into a

933
00:52:21,080 --> 00:52:28,040
Speaker 1: more rich, rich, featured product for document sharing was really

934
00:52:28,080 --> 00:52:31,560
Speaker 1: smart and so it was inevitable and I think that

935
00:52:31,920 --> 00:52:33,520
Speaker 1: they did it well and they got in there at

936
00:52:33,520 --> 00:52:37,400
Speaker 1: a good time and using that freemium model, which can

937
00:52:37,600 --> 00:52:41,879
Speaker 1: often be a double edged sword, they've really obviously been

938
00:52:41,920 --> 00:52:44,600
Speaker 1: really thoughtful about how they actually use that to entice

939
00:52:44,680 --> 00:52:50,759
Speaker 1: customers and upgrade people onto a paid platform rather than

940
00:52:50,760 --> 00:52:53,600
Speaker 1: just getting stuck in that free user only Hell.

941
00:52:55,360 --> 00:52:57,720
Speaker 2: It's probably a bit trickier to get traction on something

942
00:52:57,800 --> 00:53:01,279
Speaker 2: like that now, just because there is such an app

943
00:53:01,320 --> 00:53:04,440
Speaker 2: economy and a plug in economy. So if you launched

944
00:53:04,480 --> 00:53:07,400
Speaker 2: into the app store now, I remember writing, you know,

945
00:53:07,520 --> 00:53:10,200
Speaker 2: sort of ten years ago about New Zealand companies that

946
00:53:10,600 --> 00:53:13,760
Speaker 2: were launching on the App Store and doing phenomenal business.

947
00:53:13,800 --> 00:53:16,960
Speaker 2: You don't really hear about that anymore because they're literally

948
00:53:17,000 --> 00:53:20,759
Speaker 2: millions of apps, so it's very hard to get recognized.

949
00:53:20,800 --> 00:53:24,160
Speaker 2: What they managed to do ten years ago was something

950
00:53:24,200 --> 00:53:29,360
Speaker 2: that was universally needed. We were all using pds, and

951
00:53:29,400 --> 00:53:32,920
Speaker 2: they're at a point where these cloud operators wanted to

952
00:53:32,920 --> 00:53:35,640
Speaker 2: build out their third party offerings to make it more

953
00:53:35,680 --> 00:53:39,960
Speaker 2: sticky to be on their cloud. Luhman's timing was absolutely

954
00:53:39,960 --> 00:53:44,200
Speaker 2: perfect there, but also their commitment to improving the product

955
00:53:44,239 --> 00:53:47,480
Speaker 2: based on feedback, and that you know incredibly in twenty nineteen,

956
00:53:47,560 --> 00:53:49,520
Speaker 2: basically throwing out the code base and saying we're going

957
00:53:49,560 --> 00:53:52,759
Speaker 2: to start again from scratch. Huge undertaking to do, but

958
00:53:52,840 --> 00:53:53,839
Speaker 2: really paid off for them.

959
00:53:55,120 --> 00:53:57,319
Speaker 1: It makes complete sense and I do remember back in

960
00:53:57,320 --> 00:53:59,919
Speaker 1: the early days of Luhmen, I would find it about

961
00:54:00,000 --> 00:54:02,400
Speaker 1: clunky and it wouldn't quite work some of the time.

962
00:54:02,560 --> 00:54:05,480
Speaker 1: And the conversation has made me want to go back

963
00:54:05,520 --> 00:54:08,000
Speaker 1: and actually have a look and see what's new. So

964
00:54:08,719 --> 00:54:10,839
Speaker 1: excited to go and play with it. Have you had

965
00:54:10,840 --> 00:54:11,960
Speaker 1: a play with new Lumen?

966
00:54:13,040 --> 00:54:16,720
Speaker 2: Not really, no, but the bit that really does attract

967
00:54:16,719 --> 00:54:20,600
Speaker 2: me to it. I probably use a PDF maybe five

968
00:54:20,680 --> 00:54:23,680
Speaker 2: times a month, so I do have a Lumin account

969
00:54:23,719 --> 00:54:26,000
Speaker 2: so I can sort of edit stuff. They're basically on

970
00:54:26,080 --> 00:54:30,200
Speaker 2: the on the free plan. But you know, increasingly I

971
00:54:30,200 --> 00:54:33,920
Speaker 2: am dealing with documents where you need to sign it.

972
00:54:33,960 --> 00:54:37,400
Speaker 2: You know, it's a legal document and it's pain in

973
00:54:37,440 --> 00:54:39,360
Speaker 2: the butt. And there are all these other solutions you

974
00:54:39,400 --> 00:54:42,200
Speaker 2: see docu sign or something, or you know, there seems

975
00:54:42,200 --> 00:54:44,520
Speaker 2: to be a lot of them. So one that goes

976
00:54:44,520 --> 00:54:48,160
Speaker 2: a bit more mainstream is simpler to use. So Lumen,

977
00:54:50,239 --> 00:54:55,000
Speaker 2: you know, pdf sign, there's the signature authentication system I

978
00:54:55,000 --> 00:54:57,640
Speaker 2: think has a lot of real potential to get away

979
00:54:57,640 --> 00:55:02,080
Speaker 2: from that real corporate heavy, probably quite expensive subscription for

980
00:55:02,480 --> 00:55:07,440
Speaker 2: a document signing platform. I think there's a lot of

981
00:55:07,440 --> 00:55:08,120
Speaker 2: potential there.

982
00:55:08,440 --> 00:55:11,319
Speaker 1: Yeah, absolutely, and especially if they're able to kind of

983
00:55:11,760 --> 00:55:13,160
Speaker 1: you don't have to deal with all of the different

984
00:55:13,160 --> 00:55:15,360
Speaker 1: international standards. So if you're signing a contract with a

985
00:55:15,440 --> 00:55:18,759
Speaker 1: Singaporean company, you know you're going to meet the requirements

986
00:55:18,760 --> 00:55:21,719
Speaker 1: for Singapore and wherever else in the world. I think

987
00:55:21,719 --> 00:55:25,640
Speaker 1: that's really a useful feature that will just be innate.

988
00:55:25,680 --> 00:55:28,640
Speaker 1: Most people won't even notice it, but will be a

989
00:55:28,680 --> 00:55:30,040
Speaker 1: deciding factor for those who do.

990
00:55:30,520 --> 00:55:34,399
Speaker 2: And the government in the last couple of years has

991
00:55:34,840 --> 00:55:37,400
Speaker 2: done a big push on you know, E receipts and

992
00:55:37,440 --> 00:55:39,600
Speaker 2: all that sort of thing, so they want us collaborating

993
00:55:40,080 --> 00:55:43,839
Speaker 2: and paying for things more with other countries. And when

994
00:55:43,840 --> 00:55:45,800
Speaker 2: you get over like five thousand dollars or something like that,

995
00:55:45,960 --> 00:55:49,560
Speaker 2: typically you need to sign a document for a big purchase.

996
00:55:49,640 --> 00:55:53,560
Speaker 2: So if you can integrate that into E receipting and billing,

997
00:55:53,760 --> 00:55:56,239
Speaker 2: that's a really lucrative thing.

998
00:55:56,280 --> 00:55:59,840
Speaker 1: I think, yeah, absolutely, yeah, yeah, definitely the way of

999
00:56:00,120 --> 00:56:06,200
Speaker 1: future with this invoicing. Especially New Zealand's adopting it reasonably

1000
00:56:06,239 --> 00:56:08,919
Speaker 1: strongly now and if it can start to roll out

1001
00:56:09,000 --> 00:56:12,279
Speaker 1: better and across like Southeast Asia Europe. It's really strong

1002
00:56:12,320 --> 00:56:16,120
Speaker 1: in Europe, so it does decrease the friction of international

1003
00:56:16,120 --> 00:56:18,200
Speaker 1: trade as well, which I know is a grandiose thing

1004
00:56:18,200 --> 00:56:22,080
Speaker 1: to say about a SaaS platform, but if they can

1005
00:56:22,160 --> 00:56:26,719
Speaker 1: become a key piece of the puzzle for trade across borders,

1006
00:56:27,200 --> 00:56:31,600
Speaker 1: like DocuSign has, but do it within within an ecosystem

1007
00:56:31,600 --> 00:56:35,560
Speaker 1: of other potential useful productivity apps, then that's a really

1008
00:56:35,600 --> 00:56:37,720
Speaker 1: strong value.

1009
00:56:38,360 --> 00:56:41,799
Speaker 2: Yeah. And just finally, you know, interesting their approach to

1010
00:56:41,920 --> 00:56:46,120
Speaker 2: their development workforce. They've got teams literally all over the world,

1011
00:56:47,760 --> 00:56:52,360
Speaker 2: a significant one I think in Vietnam based on an

1012
00:56:52,400 --> 00:56:55,560
Speaker 2: existing employee who wanted to go back there. So that's

1013
00:56:56,000 --> 00:56:59,160
Speaker 2: I think increasingly the model that we're seeing. Sure, they've

1014
00:56:59,200 --> 00:57:01,919
Speaker 2: got great people in christ Church, there's a good talent

1015
00:57:01,960 --> 00:57:08,520
Speaker 2: based here. Canterbury is churning out engineering students. But thinking

1016
00:57:08,520 --> 00:57:12,440
Speaker 2: globally in terms of your workforce, Luman have definitely embraced it.

1017
00:57:12,440 --> 00:57:14,400
Speaker 2: They've got one hundred people and they're all over the place.

1018
00:57:14,800 --> 00:57:18,400
Speaker 1: Yeah. Yeah, and gosh, so much I could say about

1019
00:57:18,440 --> 00:57:23,480
Speaker 1: the benefit of being a remote work first company and

1020
00:57:23,520 --> 00:57:28,720
Speaker 1: how that can ultimately help to to give you an

1021
00:57:28,920 --> 00:57:31,320
Speaker 1: edge when it comes to expanding internationally, But then I

1022
00:57:31,400 --> 00:57:33,960
Speaker 1: might have some you know, angry CEOs yelling at me, so.

1023
00:57:34,000 --> 00:57:39,400
Speaker 2: I won't properly anyway, Thanks, so much to Max Ferguson

1024
00:57:39,480 --> 00:57:42,520
Speaker 2: for for coming on and sharing what is a true

1025
00:57:42,720 --> 00:57:43,880
Speaker 2: Kiwi success story?

1026
00:57:44,400 --> 00:57:44,600
Speaker 3: Yeah?

1027
00:57:44,600 --> 00:57:48,320
Speaker 1: Absolutely thanks Max. Show notes and the tech reading lists

1028
00:57:48,320 --> 00:57:50,880
Speaker 1: at Business Desk, dot co, dot and Z. Check them

1029
00:57:50,920 --> 00:57:52,680
Speaker 1: out in the podcast section.

1030
00:57:52,760 --> 00:57:55,800
Speaker 2: And follow the Business off Tech on your podcast platform

1031
00:57:55,800 --> 00:57:59,440
Speaker 2: of choice. We're also streaming on iHeartRadio.

1032
00:57:58,880 --> 00:58:01,320
Speaker 1: Get in touch with your feet, back and topic suggestions.

1033
00:58:01,360 --> 00:58:03,800
Speaker 1: We're on LinkedIn and Blue Sky.

1034
00:58:03,880 --> 00:58:06,680
Speaker 2: And catch us again for the next episode of the

1035
00:58:06,720 --> 00:58:08,520
Speaker 2: Business of Tech next Thursday.

1036
00:58:08,720 --> 00:58:10,240
Speaker 1: Until then, have a great week.

1037
00:58:16,680 --> 00:58:16,720
Speaker 2: M