A Product Market Fit Show | Startup Podcast for Founders
00:04:46 · Isaiah Granet
[00:04:46] S0: Yeah, that's a great question. So what's actually going on in these calls? It's really varied, and we kind of particularly play in financial services and health care, where it's really urgent. So my favorite example of a difficult call with you is a remote patient monitoring call. So this is where we call somebody, they might be ninety years old. We're walking them through putting on a blood pressure cuff, we're helping them troubleshoot that blood pressure cuff, take their reading, find it if they need to find it, plug it in, all while hearing about their grandkids, their life, any other symptoms they're having, and then taking the reading. And remember, this is on the phone, so there's no visual cue. We're taking the reading, and then we have to say, "Well, hey, they just told us a crazy number, like one hundred ninety over seventy." Are they having a hypertensive crisis, or did they put the blood pressure cuff on wrong? And how do we actually know the difference between calling an ambulance to that person's house and saying, hey, you mind just sliding it a little further up your arm or down your arm and trying that again? And these are the calls where if we don't do them, we don't do them right. It could be life or death. Similarly, we've done polls of countries where there has been recent serious unrest and we're asking questions like, are you happy with your government? And when we do these surveys, you can imagine if we were to leak the results of this, then people would be at serious risk, life and death. Those are the calls that we're talking about playing with and we don't use OpenAI, Anthropic, anybody else. So we're entirely built from the ground up. What that lets us do is be super secure and scalable. It also lets us integrate with systems really tightly. So we're reading and writing from your database, from your CRM. We're actually taking action on your behalf.
00:06:22 · Pablo Srugo, Isaiah Granet
[00:06:22] S2: But you don't use like Vapi or LiveKit or any of these things? [00:06:25] S0: No, no, we were pre-Vapi and LiveKit. Thank you very much. Yes, we are built entirely from the ground up, and that means trust also. Because there's only one provider that can go wrong, and that's us. We also don't have anyone to point the finger at, but that's why, you know, in the future, something that we want to handle is 911 calls. We want to be the first line of where you call, and we want to have that trust. And it's not just about the actions on the call, it's actually also about, on the call, we're learning live how you speak, and we're adjusting our AI speaking patterns to you using machine learning. Not just an LLM saying, what is he saying? We're actually learning from your audio patterns and figuring out how to deliver a better conversation. [00:07:05] S2: By the way, is that just a function of the fact that you started early, or would you recommend that to a voice AI company starting now? [00:07:12] S0: A voice AI company starting now should build on top of Bland but if not, I would say I would not recommend it. It was a really difficult decision. [00:07:19] S2: So you can be a piece of infrastructure, like you're not necessarily the end to end app. Silent Enterprises people can build on Bland.
00:07:24 · Isaiah Granet
[00:07:24] S0: Yeah, we have over three hundred and fifty thousand developers who are using Bland today, in addition to our a hundred and seventy plus enterprises. We do about three and a half million phone calls a week. By phone numbers, we know roughly one in four Americans has talked to Bland. Is there an element of you feeling you're running two separate businesses? Because I can understand the infrastructure pace, like, ElevenLabs or whatever. And then, actually getting enterprise and the whole enterprise sales process like there's two different worlds. What’s interesting is that we don’t think about it like that. We don’t separate infrastructure and application, and enterprise. What we really think about is we’re building phone calls, and we’re building the world’s best phone calls. And we want to make that accessible to anybody. And what the big enterprises need to be successful is a lot more handholding, a lot more in the weeds, getting direct with them, forward-deployed motion. Sort of figuring out how does this fit into the bigger picture. But that same technology can be used by anybody, really. Our job is to say, we know what a good phone call sounds like, and we refuse to allow the world to have phone trees that argue back with them. And so my short answer is, the product we build has nothing to do with the infrastructure, it has nothing to do with our application, it has everything to do with the actual call. And our real customer is the person on the other side of the phone.
00:08:37 · Pablo Srugo, Isaiah Granet
[00:08:37] S2: But then do you compete in some cases with a LiveKit or a Vapi, or an ElevenLabs, or do you take a different second to the market? [00:08:43] S0: For the most part, we really just focus on enterprise. That's the bulk of our business. That's ninety-seven percent of our business comes from enterprise and so LiveKit and Vapi have built really wonderful platforms for other people for different use cases. And, where you're going to find developers and self-serve users love us is embedding voice AI. So maybe there actually are already existing platforms, if you care about building and protecting IP. So we allow users to fine-tune the underlying models that we built, so that they can have actual intellectual property for their voice AI, and then the security reliability piece. You might end up going with LiveKit or Vapi if you're experimenting, if you're further down the stack as a solo developer, or you're a new startup just working on voice AI and you don't have any security or auth requirements yet. [00:09:28] S2: And then just to finish off that story, once they rely on you for all of the calls and you've got crazy volume going through your system. What kind of contract sizes does that lead to with that enterprise? Is that a $100K contract? Is that like a million dollar contract? What level of enterprise are we talking about generally?
00:09:28 · Pablo Srugo, Isaiah Granet
[00:09:28] S2: And then just to finish off that story, once they rely on you for all of the calls and you've got crazy volume going through your system. What kind of contract sizes does that lead to with that enterprise? Is that a $100K contract? Is that like a million dollar contract? What level of enterprise are we talking about generally? [00:09:44] S0: Good question. So our average contract value is in the six figures. Our biggest contract value is in the seven figures, soon to be in the eight figures and the craziest thing I like to talk about is most of our biggest contracts are actually with companies you would never have heard of. And what I mean by that is we work with some of the world’s biggest names. Fortune 10 businesses who are using us at scale, and they pay us a lot of money. Don’t get me wrong but the really, really big customers we have right now, the early adopters, are these businesses that are under a billion dollars of market cap. They’re generally making $100 to $300 million a year of revenue, and they spend $60 to $100 million a year on their call center. Those are the businesses who we go after and we win, and they’re willing to pay us money that never has ever been available to a software company before. [00:10:30] S2: Wouldn't the bigger, like the JP Morgan have an even bigger call center to that? Or is there a reason why these ones have the bigger spend?
00:10:30 · Pablo Srugo, Isaiah Granet
[00:10:30] S2: Wouldn't the bigger, like the JP Morgan have an even bigger call center to that? Or is there a reason why these ones have the bigger spend? [00:10:36] S0: Combined today, our current customers spend about $15 billion a year on their call center. That's just our existing part. It's a trillion dollar a year market across the globe. It is one of the most massive markets you can imagine. What I try to tell people is the call center has already been whittled down to what the minimum it can be. There's phone trees, there's hold times, there's outsourcing. If you get to a person in the United States, it's because that is it. You have found the backstop of, there's no other way to help you. There's no other way besides talking to a person in that moment and so what we focus on is these big enterprises are great and we're going to continue to work with them and deliver. But their pace of adoption is just a little bit slower and their appetite for risk is lower. What they want to see is a little bit more maturity in the AI market. We're already delivering what I would call risky calls at scale for enterprises, but they don't need to have this as a core pillar of their business. Because the fraction of their business that is call center spend is much smaller than a business making $50 million a year spending $70 million on their call center. [00:11:33] S2: It's that classic hair on fire. I mean, if thirty percent of your revenue is going to a call center, you're gonna act quick to get rid of that. [00:11:40] S0: It's a big deal if we can automate that, yeah.