George Sivulka

I think that 90% of the market is still in experimental budget phase, but we're starting to see early promises of actual value. And my entire business is focused on just those repeatable use cases.

I think ultimately the people in the enterprise that are most excited about AI and positioning it so strongly are CTOs and information technology people. And maybe the thing that Hebby has always said is that the CTO or the IT folks are actually the people that know the least about the business.

I think ultimately the people in the enterprise that are most excited about AI and positioning it so strongly are CTOs and information technology people. And maybe the thing that Hebby has always said is that the CTO or the IT folks are actually the people that know the least about the business.

I think ultimately the people in the enterprise that are most excited about AI and positioning it so strongly are CTOs and information technology people. And maybe the thing that Hebby has always said is that the CTO or the IT folks are actually the people that know the least about the business.

The people that actually understand how to use AI in a business context are those that are closest to the business. And so we're jumping the gun a little bit with the CTOs trying to build the CRM before it's been invented. And you actually need business people to build the CRM in Excel first in that order of operations.

The people that actually understand how to use AI in a business context are those that are closest to the business. And so we're jumping the gun a little bit with the CTOs trying to build the CRM before it's been invented. And you actually need business people to build the CRM in Excel first in that order of operations.

The people that actually understand how to use AI in a business context are those that are closest to the business. And so we're jumping the gun a little bit with the CTOs trying to build the CRM before it's been invented. And you actually need business people to build the CRM in Excel first in that order of operations.

And so there's a lot of unbundling of AI applications or CTOs trying to go out and build a very specific vertical application. But I actually think that building this platform, Heavy Matrix, is the thing that will unlock users' ability to discover what they can use AI agents for.

And so there's a lot of unbundling of AI applications or CTOs trying to go out and build a very specific vertical application. But I actually think that building this platform, Heavy Matrix, is the thing that will unlock users' ability to discover what they can use AI agents for.

And so there's a lot of unbundling of AI applications or CTOs trying to go out and build a very specific vertical application. But I actually think that building this platform, Heavy Matrix, is the thing that will unlock users' ability to discover what they can use AI agents for.

It's a good question. There's like four canonical prices. There's like consumption-based pricing. There's per seat pricing. There's like, hey, rent a salary, so pay a salary for an employee, which seems a little bit ridiculous, but will be less so. And then maybe there's like flat pricing. And I think it ultimately depends on how you're driving value.

It's a good question. There's like four canonical prices. There's like consumption-based pricing. There's per seat pricing. There's like, hey, rent a salary, so pay a salary for an employee, which seems a little bit ridiculous, but will be less so. And then maybe there's like flat pricing. And I think it ultimately depends on how you're driving value.

It's a good question. There's like four canonical prices. There's like consumption-based pricing. There's per seat pricing. There's like, hey, rent a salary, so pay a salary for an employee, which seems a little bit ridiculous, but will be less so. And then maybe there's like flat pricing. And I think it ultimately depends on how you're driving value.

Because Hebbia is building human-centric AI, the human layer to how you orchestrate an AI agent's staff, that scaling at inference. We do per seat because it's ultimately always back to the human. I think you'll see all of these new business models and pricing mechanisms.

Because Hebbia is building human-centric AI, the human layer to how you orchestrate an AI agent's staff, that scaling at inference. We do per seat because it's ultimately always back to the human. I think you'll see all of these new business models and pricing mechanisms.

Because Hebbia is building human-centric AI, the human layer to how you orchestrate an AI agent's staff, that scaling at inference. We do per seat because it's ultimately always back to the human. I think you'll see all of these new business models and pricing mechanisms.

I actually think that we are human first. We're business user first to the point where CTOs like to pay for consumption or API, et cetera, and business users like to pay per seat because it's how they map back to value. But also we want to incentivize change. Tech is not the hard part of all of this.

I actually think that we are human first. We're business user first to the point where CTOs like to pay for consumption or API, et cetera, and business users like to pay per seat because it's how they map back to value. But also we want to incentivize change. Tech is not the hard part of all of this.

I actually think that we are human first. We're business user first to the point where CTOs like to pay for consumption or API, et cetera, and business users like to pay per seat because it's how they map back to value. But also we want to incentivize change. Tech is not the hard part of all of this.

It's hard, but the hardest part of AI change management, no matter what company you are, are people and actually getting people to use the software. When you charge for consumption or API pricing, you're disincentivizing the change. You're saying, okay, well, I'm going to penalize you in a monetary way for every time you use an AI application. What the heck? Versus here's a per seat fee.