You're looking to raise funds to walk. How do you build up what it is that you're currently building? Thanks so much for having me. A really important thing to understand about what Gebbia does and who we are is something broader about the larger landscape. We fundamentally think that there's a problem in A.I. right now, and you have thousands of companies going out and building chat bots or search engines or things that are really great at one-off tasks. But at the end of the day, the way that we work is much more complex and happier, is building and has really built an analyst, which is amazing at doing a variety of complex tasks. It understands the way we work. Breaks it down to single steps and then can execute complex work end to end. So your problem is that, look, we're all getting hyped about A.I. and agents, but very few of them are able to do very much complex at all.

I think that's true.
Last year was this year of experimentation, but this year people
are really trying to get serious value and quantifiable value out of these A.I.
systems. And it's quite hard to find unless
you have things that can do more complex work.
A chatbot can rewrite an email or help your kids cheat on their homework.
But at the end of the day, what we have to do is we have to go and create agents
that can do complexity, that can tackle the interesting parts of what we do.
Yeah. George, I've been reading a lot about
what you've built. When I, when I think about my own sort
of day-to-day workflow, if I'm using Slack or Google Drive, I'm interacting
with files in multiple mediums, write text in documents, but also video,
audio. And often I want to like find things
across all of them. How difficult was that to build
something that can work across multiple

mediums and search across them commonly?
You're seeing a trend in AI right now where a lot of the things that people
are building, a lot of the research that people are undergoing is all around
embracing multimode ality and happier is a model agnostic.
It's hard for any firm to actually go out and say, I'm going to make a serious
bet on one model or another model. And part of the benefit that had be
provides is that the minute that multimodal models are released or the
minute that anything new happens in AI, you can leverage it immediately in a
very easily understandable way. And when when multimodal models came
out, Happy was one of the first places where leading financial firms, asset
managers and Fortune 100 companies actually ended up using those models in
production for live, quantifiable use cases that drove value.
George Bloomberg's reported that this deal values at around EUR around $700
million. Tell me about how quickly you've scaled
the business side of the company, your

sales, your operations, and how big a
challenge that's been. One of the really exciting things about
here is just how fast we've grown. We now work with over a third of the top
50 largest asset managers by AUM, and we're really planning on continuing to
grow and use this funding to become the de facto leader in generative AI for
financial services, while also going out to a variety of different verticals like
the legal vertical, where we have a variety of new customers and those
really large Fortune 500 companies that I've previously mentioned.
At the end of the day, we're coming off of 18 months of where we grew 15 X in
our revenue. Our headcount quintupled over the last
year, and I don't think it could be more exciting time to be building an AI
company right here in New York.

AI Startup Hebbia Raises $130M to Help Firms Parse Data

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