Speaker 1: Bloomberg Audio Studios, podcasts, radio news.
Speaker 2: AI startup Revo is emerging from stealth with the aim
Speaker 2: of unifying the steps and data necessary for businesses to
Speaker 2: develop and execute go to market strategies. The company has
Speaker 2: eighty million dollars from a combination seed and Series A
Speaker 2: funding round co led by Coaslaventures and Kleine Perkins. Revo
Speaker 2: CEO David Zoo and investor Vinokosler are with us now. David,
Speaker 2: I would love to start with you. You're trying to
Speaker 2: tackle the concept that you have labeled the Franken stack.
Speaker 2: Even though the term is new to me, the concept
Speaker 2: is something that's been discussed on this program a lot.
Speaker 2: Just to explain what Revo wants to achieve here.
Speaker 3: Sure, well, first off, thanks for having me. It's a
Speaker 3: big day for us. Look, AI is the biggest shift
Speaker 3: in enterprise software since the cloud, but the reality is,
Speaker 3: revenue teams are still stuck in like you said, what
Speaker 3: we call the Franken stack, which is a dozen different
Speaker 3: tools that don't really talk to each other, causing sellers
Speaker 3: to waste over seventy percent of their time wrangling software
Speaker 3: instead of talking to their customers.
Speaker 4: And that's really painful.
Speaker 3: Revo is looking to fix that via one unified revenue
Speaker 3: operating system built from the ground up with AI at
Speaker 3: its core, and with this eighty million raise, we're scaling
Speaker 3: quickly to help all companies win in the age of AI.
Speaker 2: Vinod I was talking with my team this morning about
Speaker 2: the structure of this round and so it's basically a
Speaker 2: combined seed in Series A and Revo is coming out
Speaker 2: and kind of announcing itself to the world.
Speaker 4: Would you kind of give us the backstory?
Speaker 2: You know you are an experienced investor in the world
Speaker 2: of technology. When this crossed your desk, How did you
Speaker 2: know that you needed to get involved and how did
Speaker 2: you determine at this very early stage the potential that
Speaker 2: Revo had.
Speaker 1: The opportunity didn't actually cross our desk in a traditional way.
Speaker 1: It'd be've known for a long time from door dash
Speaker 1: to open door to open store. Sorry, and now Revo.
Speaker 1: We've been incubating ventures with him. My partner Samar has
Speaker 1: worked closely with him on Revo, and we cooked up
Speaker 1: the concept, rainstormed it and thought it was important enough
Speaker 1: to do in the age of Hey, I think most
Speaker 1: applications and application stacks need to be re taught and
Speaker 1: this is David just a superstar armed to know, so
Speaker 1: it was pretty easy.
Speaker 2: That is this an example of you investing in the
Speaker 2: known quantity founder then rather than the idea?
Speaker 4: Absolutely, he wan we invested.
Speaker 1: The idea wasn't clear that was a year and a
Speaker 1: half or two years ago, but the founder was very clear.
Speaker 2: David, I'm trying to track the growth that you've had.
Speaker 2: So spring of twenty twenty four you kind of come
Speaker 2: up with the idea, I guess, incorporate a business, and
Speaker 2: you've hired I guess aggressively. You know you're sub one
Speaker 2: hundred people still, but you've basically gone to companies that
Speaker 2: are well known globally, not just here in the valley,
Speaker 2: and taken the best people you can.
Speaker 4: What was that like, Well, yeah, you're spot on there.
Speaker 3: The company you build taking a page out of Vano's book,
Speaker 3: but the company you built as the team you build,
Speaker 3: as a company you build, not the plans you make.
Speaker 3: And when we thought about tackling the space of unifying
Speaker 3: all go to market tech in one system, spanning marketing, sales,
Speaker 3: and success, we really needed to make sure that we
Speaker 3: had the talent density both from a technical perspective, but
Speaker 3: also from a go to market to really bring together
Speaker 3: the combination of the depth of domain knowledge plus the
Speaker 3: ability to access the first party data to really pull
Speaker 3: this vision off. So global talent is necessary for us
Speaker 3: to make this a reality.
Speaker 2: David, what else do you need the eighty million dollars for?
Speaker 3: Yeah, well it's over the next few months and quarters
Speaker 3: and years. Our vision is clear. We need a continue
Speaker 3: accelerating our product role map to build out both the
Speaker 3: breadth of the surface area to serve our customers, but
Speaker 3: also making sure that every single capability is the best
Speaker 3: possible from a death perspective, but more importantly, in the
Speaker 3: age of AI, context matters, and it's very important for
Speaker 3: us to double down on making sure that our AI
Speaker 3: operating system is able to work seamlessly across every single
Speaker 3: one of these modules capabilities. Job to be done, so
Speaker 3: we're not replicating another Franken stack for the future world.
Speaker 4: So that's what we're going to use.
Speaker 3: The proceeds to to do.
Speaker 2: Vinod, I go back to you with the concept of
Speaker 2: the Franken stack. You know you're invested everywhere. One of
Speaker 2: the first checks into open AI the world is changed
Speaker 2: a law since then you know, we had yesterday Shrida
Speaker 2: from Snowflake on the program talking about the problems right
Speaker 2: now and in the data layer. What do you make
Speaker 2: of the frankenstack? Is that a real thing or this
Speaker 2: is just a marketing opportunity around this round.
Speaker 1: No, I think it's a real thing. Of course, AI
Speaker 1: enables each startup to do a lot more than it
Speaker 1: could do. Twenty engineers can do the work of sixty
Speaker 1: engineers if you use the productivity tools AI enables. But
Speaker 1: more than that, the user experience can be dramatically different
Speaker 1: with the help of AI. As I like to say,
Speaker 1: in the old world of applications, users had to learn
Speaker 1: an application and they learned each vertical stack. In the
Speaker 1: new world of AI, the application learns the human and
Speaker 1: responds the way each ship. It's my favorite way to
Speaker 1: think about the transition AI makes possible. You don't have
Speaker 1: to be trained on an application, get SAP or pubs Jack.
Speaker 4: The application gets to.
Speaker 1: Know you and are the humans on your team, and
Speaker 1: so facilitates not only the function, but also work for
Speaker 1: across people and across applications.
Speaker 4: I think it's a pretty important shift in software to
Speaker 4: both you.
Speaker 2: I kind of like to end the conversation by going
Speaker 2: a little bit bigger on the world that we're in
Speaker 2: right now. You know, David, if you could reflect on
Speaker 2: what it was like doing this round. There is a
Speaker 2: lot of energy behind AI right now, but at the
Speaker 2: other end of the spectrum there is valuation concern. You know,
Speaker 2: there's no difficulty in open AI or anthropic those kinds
Speaker 2: of frontier labs gaining capital, but there is a lot
Speaker 2: going on right now. Would you just reflect on what
Speaker 2: the last few weeks has been like in trying to close.
Speaker 3: This well, you know, the fundamental difference is clear with
Speaker 3: our approach. We're AI native and purpose built for remy teams,
Speaker 3: and so you know when you talk about the old
Speaker 3: players that are trying to bowl AI onto legacy stack,
Speaker 3: it just doesn't work. What we're building with Revo is
Speaker 3: akin to how Tesla build its cars vertically integrated with
Speaker 3: AI at its core. This way, our AI is able
Speaker 3: to see, to see, and act across the full customer journey.
Speaker 3: So the old players are held back by their past,
Speaker 3: and the new players, to your point, you know, don't
Speaker 3: have the depth of domain knowledge nor the access to
Speaker 3: the full suite of first party data to pull this
Speaker 3: vision off. So Revo's building with both and yes it's hard,
Speaker 3: but that's really what makes it defensible and worth doing.
Speaker 2: You know, you're co leading this round with your friends
Speaker 2: at Kleiner Perkins. Again the same question, like what does
Speaker 2: the environment look like to you right now? This is
Speaker 2: a very sizable debut round. You had the conviction to
Speaker 2: do that.
Speaker 4: Well.
Speaker 1: It was a while ago we did the seed round
Speaker 1: of ten million, there wasn't the nuts, and now we
Speaker 1: just participated in the seventy million dollars around. Obviously we
Speaker 1: think highly of the team, but I think it's the
Speaker 1: magnitude of the opportunity this opens up for AI native companies.
Speaker 1: I like to say most valuations won't hold up in
Speaker 1: the AI space, but the ones that are really high
Speaker 1: quality companies will return disproportionate returns. In twenty eighteen, people
Speaker 1: said to me a billion dollar valuation for open air.
Speaker 4: Hours too high.
Speaker 1: Then they said twenty six billion was too high, and
Speaker 1: then one hundred billion, then three hundred billion, and then
Speaker 1: five hundred billion were all too high. So a small
Speaker 1: percentage of the companies I suspect, much less than five percent,
Speaker 1: will actually do extremely well and return ten fifty or
Speaker 1: one hundred times their money invested.
Speaker 4: Most companies will still lose.
Speaker 1: Money, and I think that's why you want to back
Speaker 1: quality founders like David. David's a superstar, right back almost
Speaker 1: anything you did.
Speaker 2: David Zo, CEO of Revo Ai Vino Cosla, co founder Coasadventures,
Speaker 2: and as we just discussed, co led that around. Great
Speaker 2: to have you both on the program. Frank, you