Saurabh Chauhan

$4 million in seed and are now selling 100 plus enterprises across APAC and US, including large publicly listed companies like Hitachi.

And yeah, it's exciting to be here and would love to talk more about what we're doing now.

Yeah, absolutely.

So I think first off, Brian, I'd probably push back on the way the industry talks about ROI.

Most AI software right now is sold at 5% to 15% efficiency gains.

And we don't see that as a transformation.

That's more or less an incremental optimization.

So I'd be sure we measured in terms of FTEs, the productivity gains in terms of FTE replaced or the cycle days eliminated based on the operation workflows that our clients run.

So typically the way it translates into customer group would be 95% accuracy in invoice data extraction, which is essentially better than humans or vendor bill payment time gets cut by 50% or customer payment cycles.

reduced by 15 to 25 days.

So we have delivered customer outcomes, which would have been using the same finance team that they currently have in most cases, but the team essentially become agent managers.

So that's not really a productivity gain as much as it's sort of creating an entire different category of software.

And even inside P2O,

Just to sort of give you a reflection, not just in what we do outward, but also inside the company, our 2026 engineering plan had initially called for 15 engineers, or we're operating that on just a team of seven engineers.

The other eight engineers are AI agents and the entire agent infrastructure is AI.

Probably, you know, one-tenth of the fraction, one-tenth of the cost of essentially adding those eight engineers.

So my test for whether an AI deployment is real is pretty simple.

Can we point to a couple of headcount that we did not hire and then the cycle days that did not get extended?

And if the answer is no and our team feels more productive, we essentially go on with that.

And it's working really well because we stopped helping humans do the work faster.