Speaker 1: You're listening to Bloomberg Business Week with Carol Messer and
Speaker 1: Tim Stenebek on Bloomberg Radio Live.
Speaker 2: Person. I don't know if you check out the share price, Matt,
Speaker 2: it was up about twenty one percent yesterday, gay Back,
Speaker 2: I think are in eleven twelve percent today's session. But
Speaker 2: the company reported earnings beat expectations, gave a forecast that
Speaker 2: was above analyst consensus for second quarter EBITDA. There are
Speaker 2: some analysts that a little bit cautious on the growth
Speaker 2: page can.
Speaker 3: Just run over ibit dah and not explain it. Does
Speaker 3: everybody know what ibit dies?
Speaker 2: Earnings before interest, taxes, appreciation, Nubritization Live Person works with
Speaker 2: the likes of NatWest, Chipotle, BT and Brewery, connecting the
Speaker 2: companies digitally with our customers. So let's get into it.
Speaker 2: Rob Locasio is back with us. He's the founder and
Speaker 2: CEOT Live Person. He's on zoom in New York City. Rob,
Speaker 2: how are you?
Speaker 4: Thanks for having me back?
Speaker 2: Well, good to have you tell us a little bit
Speaker 2: about the quarter in the outlook. What's going on?
Speaker 4: Yeah, so we beat the high end of our IBIDA.
Speaker 4: We're at the high end the rage of of our revenues.
Speaker 1: No, we basically got very focused on, like a lot
Speaker 1: of companies, you know, starting to make money, and now
Speaker 1: we're focused on, you know, turning up the growth engines.
Speaker 4: We just launched our new generative.
Speaker 1: AI products last week, so a lot of excitement at
Speaker 1: the company.
Speaker 2: I just want to just follow because a lot of
Speaker 2: there were a few analysts that actually cut their price
Speaker 2: targets on you guys today by an average of seventeen percent,
Speaker 2: and the stock is down about fifty percent. There's two
Speaker 2: sales tenholed. I'm just curious, what is it that you
Speaker 2: think the investment community is potentially missing or what do
Speaker 2: they hammer you most about.
Speaker 1: We did a big restructuring last quarter, and we even
Speaker 1: we took out about seventy five million in revenue that
Speaker 1: was not on core and we.
Speaker 4: Even sold a business.
Speaker 1: So I think it's really the investors digesting taking that
Speaker 1: much revenue out.
Speaker 4: But then we got positive eve DA and now we're.
Speaker 1: On a path for a positive cash flow as a company, So.
Speaker 4: So that's I think they just got to digest it.
Speaker 1: Yesterday we did what we said we were going to do.
Speaker 1: This will be the four I'll call it the first
Speaker 1: clean quarter and now we're kind of off to the races.
Speaker 3: I mean, I think a lot of companies rob that
Speaker 3: did really well during the pandemic like you did. I mean,
Speaker 3: whose stock did really well during the pandemic have just
Speaker 3: gotten crushed since then and brought down below twenty nineteen
Speaker 3: levels because the pendulum swung too far in both directions, right,
Speaker 3: I mean, you were trading for forty bucks a share
Speaker 3: at the end of twenty nineteen and now it's four
Speaker 3: sixty five. What do you think it's going to take
Speaker 3: or how long until you can get back to those
Speaker 3: pre pandemic levels.
Speaker 1: Look, we have a very you know, good sound strategy,
Speaker 1: which is, you know, with the leader in enterprise AI
Speaker 1: and working with the biggest brands of the world and
Speaker 1: now AI and everything around Jenner of AI.
Speaker 4: Is about the hottest thing that you can expect.
Speaker 1: So I think for us, there's win in our sales
Speaker 1: to continue to actually to you, you're right, there's a
Speaker 1: disconnect right now. But you know, we just got over
Speaker 1: the next couple of quarters, I think two or three
Speaker 1: quarters re establish our growth rates and then you know,
Speaker 1: then we could get back to those you know, pre
Speaker 1: pandemic rates.
Speaker 4: But the pandemic. We grew like weed.
Speaker 1: You know, contax centers shut down, they need to do
Speaker 1: messaging in chad in AI and bots, and we were
Speaker 1: at the right place at the right time, with the
Speaker 1: right tech. Obviously that growth has come down, but now
Speaker 1: there's generated AI and that's a whole other way of growth.
Speaker 4: So that's really what we're focused on.
Speaker 2: So HOLP was that like, you know, when you say
Speaker 2: that you're the leader in enterprise prize AI and you
Speaker 2: are working with some well known companies. When you have
Speaker 2: an average deal, what kind of revenue do you book
Speaker 2: on that and what kind of visibility or long term
Speaker 2: visibility does it actually ultimately give you.
Speaker 1: Yeah, So our our poofs around six hundred and seventy million,
Speaker 1: six and sixty million, six and sixty thousand, but an
Speaker 1: average enterprise customer paces anywhere from three to ten million
Speaker 1: dollars a year. And this would be a large bank
Speaker 1: and large telco insurance company. And they're really using it
Speaker 1: to drive the transformation from traditional voice calls into digital.
Speaker 1: And now what they're looking at is how do we
Speaker 1: automate those conversations at a very high rate.
Speaker 4: And we've been able to do a very good job
Speaker 4: up to now.
Speaker 1: But with all the generative AI stuff, we're going to
Speaker 1: be able to automate conversations.
Speaker 4: And we just even released a thing.
Speaker 1: Called Voice AI that we can automate voice conversations. So
Speaker 1: this is really, I think an interesting time for us
Speaker 1: on the product side and the platform side.
Speaker 3: We talked to the CEO of gup shop yesterday and
Speaker 3: they do this kind of thing for Verizon and City,
Speaker 3: and I have to say I fully body slammed the
Speaker 3: technology because I recently had a problem with Verizon and
Speaker 3: I noticed, I mean, the bot doesn't work, it's not
Speaker 3: giving me anything, and I would honestly like pay money
Speaker 3: to be able to skip past that part and just
Speaker 3: get to the agent, the human agent that I want
Speaker 3: to talk talk to. How long until rob this technology
Speaker 3: works well enough that you know, somebody with specific problems,
Speaker 3: not just FAQs, is going to be satisfied talking to
Speaker 3: AI rather than and even maybe prefer talking to AI
Speaker 3: than a human.
Speaker 1: Well, I mean, look, we do a billion conversations a
Speaker 1: year and where there's seventy five percent of us have
Speaker 1: automations and twenty five percent automations, and so you're right,
Speaker 1: bots to me is a four letter word, but the
Speaker 1: way we do it with our customers because we have
Speaker 1: a very rich set of tools, we also have this
Speaker 1: amazing data set, we're able to do very high quality automations.
Speaker 4: With our customers.
Speaker 1: So the generative AII stuff, when it does, it just
Speaker 1: opens up a lot more on the long tail. Like
Speaker 1: we were looking at one of our airlines and we
Speaker 1: have a lot of the biggies and we found people
Speaker 1: ask about iguanas like I'm looking for an iguana, So
Speaker 1: I'm looking to take an iguana on the flight. And
Speaker 1: we would never write a bot for that. But the
Speaker 1: large language models hits the data set and comes back
Speaker 1: and then gives a reply like it's they have to
Speaker 1: be forty five pounds or less.
Speaker 4: We're going to guana on a flight. So this is
Speaker 4: the stuff that's really powerful.
Speaker 1: You take the data set and the models, and the
Speaker 1: models are basically taking the data set and making them
Speaker 1: conversational without building a bot.
Speaker 4: And bots will go away. You know, they'll eventually go away.
Speaker 3: That's awesome. You know, the average weight of a male
Speaker 3: iguana is eight point eight pounds according to that.
Speaker 4: You know, Rob, now he's going I saw it was
Speaker 4: under forty five.
Speaker 2: He's now gone down an iguana rabbit hole.
Speaker 3: I really want to be sitting locked to somebody on
Speaker 3: my next flight.
Speaker 2: Oh lost him. I want to ask you something. Enterprise
Speaker 2: AI roughly almost seventeen billion and twenty twenty two in
Speaker 2: terms of market size. I think that's a global market size.
Speaker 2: We're looking at maybe one hundred and three billion by
Speaker 2: twenty thirty. Maybe it gets even more with all of
Speaker 2: this excitement over generative AI. But you are dealing with
Speaker 2: some big players Microsoft, IBM, Salesforce, and Video Like. There's
Speaker 2: a lot of people that are involved in it, not
Speaker 2: all of them are enterprise AI exclusively. How do you
Speaker 2: ultimately compete against some of these bigger players who again
Speaker 2: going back to you know, those bigger players who are
Speaker 2: doing this kind of day in and day out, are
Speaker 2: maybe going to be a cheaper option and maybe a
Speaker 2: better option.
Speaker 4: Yeah.
Speaker 1: Look, we're I would say there's about ten of us
Speaker 1: in the race of enterprise AI.
Speaker 4: You named a few of them. What makes us unique
Speaker 4: is we've got a.
Speaker 1: Data set that's one of the most comprehensive and detailed
Speaker 1: data sets around conversational add these are chats transcripts. If
Speaker 1: you want to power high quality conversations. You need that
Speaker 1: data set, and we have the largest data set out there.
Speaker 1: The second part is we're starting to build tools so
Speaker 1: other people in the organization can get access to that
Speaker 1: data set. For instance, one in marketing can say, tell
Speaker 1: me today why people are not liking us or our products,
Speaker 1: or tell me the top ten reasons that the website
Speaker 1: is having issues, or build a marketing.
Speaker 4: Campaign that I could sell.
Speaker 1: Let's say, tell sell service to families in New York
Speaker 1: and it would generate the ad campaign. And so you
Speaker 1: have to be able to do that using the unique
Speaker 1: data set. And what makes AI powerful is when you
Speaker 1: have the language language model, right plus the data set,
Speaker 1: and the data sets like half of the problem.
Speaker 4: And we have one of the best data sets in
Speaker 4: the world for business outcomes.
Speaker 3: It's true. We heard that from Ed Ludlow yesterday. He
Speaker 3: was at Google in Mountain View and he said, the
Speaker 3: data set is key.
Speaker 1: Wow, the data sets can and I think you're going
Speaker 1: to see their companies just valued on the data sets.
Speaker 1: Like if one day that the value of our company
Speaker 1: could be what is the data set? How much is
Speaker 1: that worth? It's tremendous because it delivers these business outcomes.
Speaker 2: Right, which is why exactly any McAfee talking about right,
Speaker 2: this stuff is only as important as the data you
Speaker 2: put into it, the amount accumulation of data, and it
Speaker 2: just gets smarter and smarter.
Speaker 3: Got to have the IP.
Speaker 2: Got to have the IP. Rob, Thank you so much.
Speaker 2: Fun to check in with you again, Rob the Cossio.
Speaker 2: He's a founder and CEOT live person joining us on
Speaker 2: Zoom in New York City. Yeah, it's what.
Speaker 4: Are you going to do?
Speaker 3: We're talking about A again. We should do a whole
Speaker 3: show on A. We should just do an hour, one
Speaker 3: hour nightly show on artificial intelligence.
Speaker 2: Isn't that isn't that coming?
Speaker 3: Yeah, we should have an AI. I would do A
Speaker 3: do the show because you.
Speaker 2: Just want to get home earlier. But it's about No,
Speaker 2: it's it's fascinating. I mean, like all of a sudden,
Speaker 2: the conversation. I think about the last year or two,
Speaker 2: like right, we were all kind of all in on
Speaker 2: crypto and we're all obsessed with that, and I'm still
Speaker 2: all in. I know, I know you are, and we're not.
Speaker 2: We're still figuring that out. But now it's all about
Speaker 2: AI generated it just moves along.
Speaker 3: The two can work together, Yes, they AI can work
Speaker 3: with the blockchain.
Speaker 2: A I could maybe make crypto work. Maybe maybe there
Speaker 2: you go.