Takeoff founder Aakash Thumaty on going from $0 to near-8-figures in revenue before being acquired by Sierra

Speaker 2: Own the data platform that powers it. And let me also tell you about Cisco, critical infrastructure for the AI era. Unlock seamless real time experiences and new value with Cisco. Up next, we have Aakash from Takeoff. He's the founder and CEO. He's been on the show before, but this is the first time

Speaker 3: Here he is.

Speaker 2: With a new flag. How's it going? Give us the news.

Speaker 1: It's going well. It's great to see you guys. The news is that Sierra just bought us.

Speaker 5: We announced it last Thursday.

Speaker 1: Jordy completely missed.

Speaker 2: That helped me.

Speaker 5: Let's go.

Speaker 1: That's the first first miss. First miss.

Speaker 2: Brutal. Well Sorry to do that. Congratulations.

Speaker 1: I gotta go back go back to practice. Work on this. So No. I'm excited. I'm excited. Thank you, guys.

Speaker 2: So tell us the story of the company. I mean, we got got enough time for, I think, for you to tell the entire story from start to finish because all of this sort of happened pretty quickly. Where were you before you started the company? When did you start the company? What was the growth like? Take us through the the the journey.

Speaker 5: Yeah. Absolutely. So we started the company a little over a year ago. We started to build Over a basically like agents that would be slightly more Yeah. Capable than what we're seeing today. Sure. Right? I we fundamentally founded the company on this hypothesis that there were two different kinds of agents. There's human in the loop agents. Mhmm. And then there's truly autonomous agents. Mhmm. Human in the loop agents are the agents that we all love to talk about. Like, we're talking about plot code, codex, things that you prompt. They do things. They can do them for a very long time. It could be minutes, dozens of minutes, hours, even some case in some cases days. But fundamentally, you are the person that kicks them off and evaluates their work. And then, like you were talking about in the previous interview, clicks accept, viewing my downloads folder. Yep. Autonomous agents are not that. Yeah. Autonomous agents, when you think about it from the perspective of a buyer, it should feel like you are multiplying your labor force. And when I say feel like, mean it should be a one to one translation. Yeah. I should feel like when I buy takeoff, I'm buying a 100,000 agents that can do what I might have a team of disparate human software, etcetera, doing today

Speaker 2: Mhmm.

Speaker 5: But at a much more massive scale. Yeah. That was like the foundational thesis of like, how do we actually build agents that can do this? We call them long horizon agents. We call them fully autonomous agents. And they would go after explicitly revenue aligned use cases. And the reason we went after revenue aligned use cases is well, there's lot of different reasons. But the most obvious reason is like, why are you going to buy mission critical AI software from a kid with crazy hair? Like, the only thing that's going to get you to do that is if I can prove to you I'm going to make you more Mhmm. Right? And the

Speaker 3: way I get and the way

Speaker 1: I get to prove to you I'm going make you

Speaker 5: more money is I make it very zero risk for you. I'm like, give me your lowest quality leads if I'm talking to a lending company. Give me your patients that are going to, churn Mhmm. If I'm talking to a healthcare company. And, like, let's see what I can do with the agents that I build for your company. Let's see if I can recuperate that lost revenue. Let's see if I can increase your top line. Mhmm. And if we are all successful here, at the end of the day, I'm going to be in your board deck at the end of the year because you bought a piece of software and revenue is up double

Speaker 1: Yeah.

Speaker 5: That was the foundational pitch thesis, the whole idea of what the company was going to be. We tried building agents in different in different ways. We started actually with browser agents because we figured if we can use software, we can do what humans do. Yeah. But we thought that that would actually we we realized, not thought. We realized because we get spit eaten up, chewed up, spit out by the market over and over again. Mhmm. We realized that that's Over

Speaker 2: and over again for like for like six months.

Speaker 1: For six months. For six months. That's fair. One simple tax rate.

Speaker 5: For for the viewers, what Jordy and John are referring to, if if you haven't read our literature, which I don't expect you to, is that we entered this calendar year at effectively $0 in committed revenue. And by the time we got acquired by Brett and Sierra, we were at near 8 figures in revenue. So what they're referring to is that very short and vertical kind of, no pun intended, takeoff in revenue ramp.

Speaker 2: Let's

Speaker 5: go. And so, again, More like people

Speaker 1: should name their company takeoff.

Speaker 2: Great that's a lesson. It's amazing.

Speaker 1: Yeah. I mean, it it's got

Speaker 5: its own SEO things. Former member of Migos, rest in Yes. Now, we're we're honored to, like, carry the name with a positive light. That being said, like, you're only gonna make money if your agents are trying to sell or, like, you know, trying to be sold upon the value of adding revenue if you actually add revenue. And so we de risk it because I know, I'm not Bret Taylor. I can't walk into a room or at least I couldn't walk into a room previously and get someone to pay for something that's not already driving results. Mhmm. So we go in, we do pilots. They're not necessarily free, but they're paid on outcome. Mhmm. And so if I drive this outcome that we're talking about, usually directly revenue or something tied to revenue Mhmm. For example, for a lending company, loans funded, loans originated

Speaker 1: Yeah.

Speaker 5: I get, you're going to pay take off the way you pay a human being on commission and some sort of base units based on the amount of tokens, voice, SMS that are used. So the customer thinks, I'm only paying when I create x thousands of dollars in margin. I'm paying hundreds of dollars of cost of goods sold. They love that trade off. And they're like, if it fails, it fails. And if it succeeds, we're making more money at the end of the year. Yeah. That's how we keep Crazy Hair walks into a room and ends up selling multimillion dollar contracts over and over and over again. Because like, once it starts actually working

Speaker 1: Yep.

Speaker 5: Even what I did not expect, really, is like the compounding nature of of of exponential growth.

Speaker 2: I love it. Walking I through

Speaker 3: love you guys that question.

Speaker 2: How deeply you're integrating or you were integrating with some of those first customers. Because there's a world where you're just like, give me the stale leads. I will go off and I will do the email. I will do the SMS. I'll do I'll do the whatever happens and I'll sort of like either build my build those systems or maybe you'll set up your own like Mailchimp account or whatever you want. Or there's another version where you're like, I just I want to live within your CRM, within all your tools. I will do API integrations into whatever legacy systems you have to actually Yeah. Collect all the knowledge to make the correct move and actually drive revenue.

Speaker 5: No. It's a fantastic question. And it was it's categorically the latter.

Speaker 2: So Okay.

Speaker 5: There was this there's this lecture, for lack of better words, give for every potential candidate and existing employee

Speaker 3: Mhmm.

Speaker 5: Of Takeoff, which is we are given the privilege, Right? Not the right, but the the sheer privilege of sitting between our customer and their revenue.

Speaker 2: Mhmm.

Speaker 5: Like, I could explain this in a million ways why it's so important, but the most important thing to explain is that our buyer was always the CEO or a c suite member. It wasn't some VP of something that reports into something that reports into the CEO. When you are selling revenue, you are selling to the CEO.

Speaker 1: Mhmm.

Speaker 5: That's what he or she is getting greater on at the end of the year. Whether they're a public company of which some of our customers are, whether they're massively multi billion dollar private company. They're getting graded on revenue and then Sean's

Speaker 2: fired at the chief revenue officers in the audience, but No. No. I know. I know. I'm pleased with you.

Speaker 3: It's it's I mean,

Speaker 5: it's one it's

Speaker 2: one of

Speaker 5: the things Brett pointed out. Brett, like, it's kind of amazing that, like, every one of your customers, your contact, like, person who's in my iMessage, top five iMessage is the CEO. Yep. And so, like, to answer your question, I would give this lecture that when we are referenced by our customers Mhmm. They have to think of us as their best employee. When I say us, I mean myself, like Aakash, Spencer, Shred, my teammates names.

Speaker 1: They have

Speaker 5: to think of us as their best employee. And the way we get there is we have to understand their business Mhmm. As well as any individual that works for them. They could be a 10,000 employee company. They should be able to ask us about anything that is even remotely related to the line of work that our agents are doing for their business, and we should be able to answer it. I'm talking about gross margins. I'm talking about conversion rates. I'm talking about, time to fund. I'm talking about time between first contact to revenue generated. Literally everything. And we know we've succeeded when the CEO starts asking us questions about their business. Mhmm. That's when you're in like, you know, the the promised land. That's when you are literally their friend when they're texting you 05:30 in the morning, 10:00 at night, and like none of your family or friends are in your top five iMessage anymore. It's just your customer's CEOs. Mhmm. And so, it's very much understanding like the intricacies of that business in order to build an agent that could actually do what's going to drive that company's revenue. And so we have to understand every every piece of software that they're using, every single thing that somebody might do because we are trying to genuinely scale the workforce. And you can only scale the workforce if you can do it end to end. And that's like a really important thing that I think most agent companies don't get. If you're going to sell an agent into some work stream, but you're only going to take like a horizontal slice, it's virtually useless because then you have to educate everything below and above it how to drive the end to end results. Mhmm. So if you want to actually drive the business outcomes, own the whole thing. If wanna own the whole thing, have to be capable of owning the whole thing Mhmm. Which means you have to understand the business well enough to build the agent to do so. You guys had Markey, who's been a friend and incredibly Yeah. Incredible founder who I've learned a lot from on the show, I think a month or two ago.

Speaker 1: Yeah.

Speaker 5: Yeah. And Markey talked about how her entire company and product is rooted in this foundational philosophy that we have to translate whatever language the company is speaking to what the agent is going to do. Yeah. But we think very, very similarly. Our culture is entirely predicated on that assumption that if we don't understand the business better than our customer or as well as our customer, our agents aren't going to do it as well as we need them to.

Speaker 2: So what does that translation look like for you? Is it a bunch of markdown files and then your agent can interpret those? Because you could go all the way to like, we pretrained a model just for you. And then we can be like, we fine tuned a model for you, sort of the thinking machines model. And then you could be like, well, we're using, you know, the frontier models, but we have a custom harness for you or we customize our harness for you or we write a special integration or it's just or the agent just shows up and it figures it out.

Speaker 5: I love that you're giving multiple choice because if you didn't, that would just, like, ramble. It is the second half of answers that you

Speaker 1: just said. Okay.

Speaker 5: It's like another foundational philosophy that we kind of built this company on is that the inference API is a commodity. That's a sound bite. You can clip me. That'd be great. And that's

Speaker 1: a crazy thing to say. Right? It's a crazy thing

Speaker 5: to say that inference API is a commodity because we think about cloud and Anthropic Yeah. Anthropic and OpenAI at tens of billions in revenue. Yeah. People are gonna be like, that's all inference. Yeah. I would disagree. I would say it's a function of the things built on top of inference. Talking about TBP, clod, codex Interesting. And clod code.

Speaker 1: Yeah.

Speaker 5: And, what we need to be able to do is and you can call these most people would call these harnesses. Right? Like harnesses with like a great GUI with a great command line interface. But it's functionally the thing that's delivering end to end value. Mhmm. And like coding was a great first coding and chat agents were a great first product Mhmm. Because that was the end to end value. Again, it's a human in the loop type agent. So they are giving the value to the person that's using the product. Yeah. The second the subsequent type of, like, wins in enterprise AI. And when I say wins, don't mean, like, hundreds of millions in revenue or even billions. I'm talking about, the next wave of tens of billions of revenue. Mhmm. It's going to come from the fact that your harness, which is just a fancy way of saying agents that can do multiple things and operate across multiple different services surfaces as opposed to a single a call and response API, could be as capable as someone that is, like, is on a job listing or, like, something that you were hiring to drive an outcome or a result for the business. And so it's a combination of harnesses. Specifically at takeoff, what we built was what we call it is a DSL, a domain specific language. Right? So you should be able to educate, direct, and build the agents on takeoff using our domain specific language that is built around the idea of we're trying to handle something end to end. Mhmm. The other kind of like unique thing about this is like your agents have to be answerable to the outside world. Like, you can't just say go do a thing. Mhmm. The thing that you are that our customers are calling APIs for is go fund this loan or an API call to go onboard this patient or go get this patient's prior authorization. That requires multiple actions by the agent that then in turn require input from the outside world. Let's use the borrower example, the loan borrower. If you're getting an API call to your agent that says, go fund this loan for this borrower, this lead, you have to call that lead, contact them, help them with that initial, like, rate quoting, understanding what options they have, whether it's a HELOC, a refi, a home equity loan. Then you have to have a second call after whatever happened in between the first call and the second call. You have to go reach out to third parties, the e notaries, the underwriters, everything else involved, document collection. Then you have to have a third call saying, hey. I noticed you got stuck here because you have this, like, weird Iowa borrower question about co borrower cosigning. Then you have a fourth cause, getting it over the line for funded. Yep. This is something that for an agent to actually handle end to end, your harness is like is is transcending just like tool calls.

Speaker 2: Mhmm.

Speaker 5: Right? It's like it's an always on harness with a heartbeat that's answering anything that could happen by, on behalf of, or in relation to this, like, central entity in this example of the borrower.

Speaker 2: Tell me a little bit about post merger integration. I could see Yeah. Sierra having a product called Takeoff. I could see Sierra just being a service or company that you work with for a bunch of different things. I don't even know if I need different products because AI is so broad that everything sort of merges together into, one product that can do multiple things. And I just flip on a switch and say, okay, I want you to handle this. I want you to handle this. But how are you thinking about integration? I know it's I know it's like really, really early, but

Speaker 3: No. It's it's what is

Speaker 2: I I imagine that this was what you were talking to Brett about was like with a vision of what these two companies can do together. So like take us through a little bit of it.

Speaker 5: Well, I mean, that's actually great. I'm gonna go in reverse order of your questions here. Like, when when Brett and I first chatted, we basically realized that we have a similar vision of what the world was headed towards. Mhmm. And what we realized was that by virtue of just, again, being a kid with crazy hair, like, there's no chance that I was gonna, like, compete and win in customer support. There's a dozen companies, three of which that are like

Speaker 1: Selling yourself short. Seem you seem to me, I'm I'm getting young Bret Taylor. Yeah. Let's pull up a picture

Speaker 2: of Bret Taylor's hair, please, and see if you can When he was

Speaker 1: your age.

Speaker 2: Hair. I think you got a I think you got a shot, but yes. Okay.

Speaker 5: The point being that like we had to come from a different

Speaker 1: angle, right? Yeah. We had

Speaker 5: to sell a thing that only the early adopters were ready for. Yeah. And like like, it's not like we and so like, I when I say we had a similar vision of the of the direction the world was headed in

Speaker 2: Sure. Like, we

Speaker 5: were further along on that timeline. Yep. And like, we had done this thing that I don't think most of the world realized was possible yet. Yep. And it wasn't till we proved it was. Right? Mhmm. That's what was really exciting to, I think, Brett and the company is

Speaker 2: like Sure.

Speaker 5: Hey, we'd love to get to where you are, but we're realizing that you're already there. And why not get there together and then scale at times a million?

Speaker 1: Sure.

Speaker 5: Right? And so, that's kind of the original conversation started. Mhmm. We then kind of came to this like realization that and I think what was actually really interesting for you guys to understand or for anyone who's listening and watching is that we realized we were onto something when our first like $3.07 figure customers were like, already had customer support vendors. Right? That they had like a Sierra or a Decadron or something else They were spending on average between a few $100 to maybe like maybe a million dollars with them. With us, they were spending at least three times more.

Speaker 2: Wow.

Speaker 5: Right? Like, had they had an AI support vendor and they also had Takeoff. They were spending three times, in in one case, eight times more Yep. Than they were spending with their support vendor.

Speaker 2: And that makes sense because you're driving revenue

Speaker 5: and you're Exactly. Talking And if you're driving revenue and there's three kinds of software. Right? There's revenue driving software, there is functional software, and then there's must have software. Yep. And if you're the first category, Google Ads, Facebook Ads

Speaker 1: Yep.

Speaker 5: $1 in equals more than $1 out, I will keep spending till I flat that line. Yep. And that's what we were going for. It's exactly how we want to be thought of by our customers. Yeah. And so we realized, you know, again, all the things that Brett and I were talking about that we were excited about, a lot of the same similar shared ideas around where the world was headed. We're like, hey, together this can be one full of 20 with a thousand. And so we we I don't know if you guys saw it probably not because you have a lot going in your mind. We we as in Sierra and take off the Sierra together launched this product called Horizon

Speaker 1: Yeah.

Speaker 5: Which is this new thing. And the reason it has to be this net new thing is because we want people to realize this is a step function jump in capability. Yeah. A step function jump in capability which is going to drive revenue for your business.

Speaker 1: It's not just agent in, like, one second cost savings,

Speaker 5: but it's agents that your CEO is buying. Yeah. And that's really freaking exciting. Yeah. Don't I know if I can swear. I'm sorry. No. No. But that's really exciting.

Speaker 2: That's awesome. Yeah. No. It makes it makes so much sense.

Speaker 1: Great at you're great at naming.

Speaker 2: Yeah. Yeah. These are all every every name is great. Like, these are all good. Yeah. I love them. Well, thank you so much. Jordy, anything

Speaker 1: great to meet you. Yeah. I found the I found the the whole pitch very compelling. I was just imagining myself as a as a CEO or enterprise buyer being like, I'm sold. Just send the contract. Send the contract.

Speaker 5: I will say, like, I've been on a few sales calls with Brett now, and Brett it's very flattering to hear this from Brett Taylor. Right? Like, of the best salesmen that's probably ever lived in software's history. We've had a few sales calls together. It is magic in that room. Like, people get really freaking excited when we show them Horizon. It's like, And it is like people start imagining what they're going to be doing for their business. Yeah.

Speaker 4: All the

Speaker 5: awards they're going to get. The fact that in the board deck it's going be plus double digit percentages at the end of the year. Yeah. And that is very exciting for us as a company.