Fireworks AI raises $1.5B to build the specialized AI inference and training platform for enterprise

Speaker 8: We got the entire company to be super AI pilled, spending a lot of lot of money. Maybe they don't want me to say the exact number. But now, obviously, like, we're we're taking a step back and and looking at the costs and and the outcomes and looking at way ways that you can kinda optimize. And so we're building this product with our finance team hand in hand. We're sitting next to them every day and and showing them, hey. Like, here's how we've done the optimization for this workflow, or here's here's how we've done the semantic tagging for our internal background coding agent inspect. And so it's been really fun, honestly, to use this product. And I think that's what makes this product really good is that we've built it for ourselves and can share the learning along the way.

Speaker 1: Fantastic. Well, congrats on Great to finally meet you as well.

Speaker 2: Steve Ings and great to meet you.

Speaker 3: Yeah. Yeah. Thanks for opportunity the show.

Speaker 2: It makes so much sense. It's an exciting expansion. Will talk to you soon. Have a great week. We'll talk to you later. Goodbye. Let me tell you about public.com. Investing for those that take it seriously. You got stocks, options, bonds, crypto, treasuries, and more with great customer service. Our next guest is the cofounder and CEO of Fireworks AI. Let's bring in Lynn. It's been too long. How are you doing?

Speaker 1: What's going on? Show. Hey.

Speaker 9: Thanks for having me.

Speaker 2: Thanks so much for hopping on. Give us We the missed the fundraising announcement, but we're glad to have you here. How much did you raise? What happened?

Speaker 9: Yeah. We raised 1,500,000,000.

Speaker 2: Wow.

Speaker 3: Good

Speaker 2: job. Jordy from downtown.

Speaker 1: Not not my best shot,

Speaker 2: but got it done. It's incredible.

Speaker 1: Massive. Talk about talk about everything that's happened since the time you're on the show. It feels like it's been at least six months, maybe closer to twelve, but you guys have been super busy. Cooking.

Speaker 9: Right. So we we focus on building specialized intelligence platform. Mhmm. What that means is we want to make sure every single company has a tool to protect their alpha Mhmm. And to turn their alpha into their own intelligence.

Speaker 5: Mhmm.

Speaker 9: So what does that mean? Is we build a training and inference platform, co optimized, co designed together to allow application enterprise, activate their private data, continuously turn that into their customized model, optimize for inference for both speed and cost, where they, to solve their specific problem, they should have the best model quality, the best speed, and significant lower cost of our operation. By that, I really mean five to 10 times lower cost for them to build a durable business. We see an interesting dichotomy in current AI time very different from SaaS time, where at SaaS time, product market fit and a durable business is one thing. Once you hit a product market fit, you scale as fast as possible. I think last time I mentioned, in AI time, once you have product market fit, you're likely to scale into bankruptcy. You guys laugh at that. Yeah. Yeah. And that's become reality

Speaker 2: right now.

Speaker 1: So so funny.

Speaker 9: So this is not just startups. Many startups are really facing the jeopardy of scaling into bank's bankruptcy even though they have a great product. It also is happening to large public companies because they are the winner. They were the start up, and they are winner winning various different kind of solution space towards cuss consumer, prosumer developers. They have a huge amount of traffic. If they deploy their AI features to all their audience, it's a lot of a significant amount of cost. And they also get stuck and not able to roll out their AI features. So at the same time, we know that application development has been significantly disrupted. It's very easy to implement ideas or copy ideas by because writing code is no longer a barrier. Yeah. We want to make sure had an interesting conversation with Jensen after his g g DCC keynotes. He mentioned there's no special general company. There's no special general company as in every single company exists for a reason. Mhmm. The reason for a company to exist is they specialize in solving a particular problem extremely well. And that offer exists from the product design to their business operation to their deep understanding of their customer and all of that reflecting private data. And today, every single company should have full control of how to turn that private intelligence into a model they can operate and power their product. If they only build on top of a black box API via API wrapper, it there's really hard it's really hard for them to do build up durable business. So we want to give our customer the best tool to build a specialized intelligence, to have full control of their own intelligence, to stand on top of and have full control of the cost for them to scale in the long run. So that's what we're doing and that's where we're gonna use our new fundraising to deploy capital into to accelerate that pace.

Speaker 1: What's the biggest bottleneck to your business? What's you're growing quickly, but why aren't you growing faster?

Speaker 9: That's that's part of the reason why we're raising this round is capacity. So we are the whole industry is going through a super linear growth Yeah. In terms of demand. It's because of doesn't matter whether it's open, close, the model quality pass the threshold of solving many, many problems. And on top of that, the tuned model quality is even better. And we as a company, we need to grow significant amount of capacity of people across the board. We're hiring from researcher to engineers to marketers to sellers, top notch. And we invite passionate people to join us on our mission I of building specialized intelligence.

Speaker 2: I saw someone talk ask for, like, we need a Costco of AI, less philosopher kings. Do you like the idea of becoming the Costco for AI?

Speaker 9: That's an interesting analogy. I think at the end, what we believe is the whole entire industry is changing from token maxing to value maxing.

Speaker 2: Sounds like Costco to me.

Speaker 1: That's right.

Speaker 9: Because at the end, not all the tokens are equal. Yeah. And we care about solving a specific task, use the most economical way to approach it. Yeah. That's a doable business. And it has there's nothing new here. In the past, you know, hundreds of years of capitalism Yeah. Capitalism was designed for efficiency.

Speaker 2: Yeah.

Speaker 9: And and I I think the whole ecosystem is really good at that.

Speaker 2: So And

Speaker 9: that's the Costco trend

Speaker 2: has, you know, other brands. They have the Kirkland brand. They've done some vertical integration. How deep does vertical integration go? How important is vertical integration to providing the lowest possible cost and winning on essentially value?

Speaker 9: Yeah. So as we from our point of view

Speaker 1: Yeah.

Speaker 9: There's so many innovation that's happening on top of us. Many of those are application doing vertical intuition.

Speaker 1: Sure.

Speaker 9: And we are powering them today Mhmm. Including in in public. We talk about cursor because I've been training their own model for a long time. Yep. We talk about Harvey. Harvey have been training about their legal model for a long time. Yeah. There are many many other customer cross coding, co work, all kinds of co work verticals from legal, finance, recruiting, marketing, sales, customer support. Yeah. Wide variety of vertical. They are all building all sorts of vertical solutions, and they have their unique insight to build their customized model and make their business really standing out.

Speaker 2: Yeah.

Speaker 9: On top of that, there's also a lot of consumer facing company, and the whole entire entire industry is literally going all in on AI in production where we are helping them to transition

Speaker 2: Yeah.

Speaker 9: Into embracing not just embracing AI in the proper way, but but really integrate their offer Yeah. Into their

Speaker 2: Even when you see Google search overviews, like, that has to be extremely cheap. Like, they don't charge for those. Obviously, Google is completely vertically integrated down from model training to they have custom silicon. They have their own data centers. Is that where you think it goes? Do you think you'll do custom silicon, your own own data centers, have power generation contracts to, like, fully offer the cheapest possible product for a particular category?

Speaker 9: So I'm humble enough to acknowledge there are tons of experts

Speaker 2: Yeah. Yeah.

Speaker 9: In every single layer Yeah. Of this AI innovation. I think Jason mentioned five layer cake. I think there's probably more than five layers if you

Speaker 2: Woah. Look

Speaker 9: looks a

Speaker 2: lot. Shot fired.

Speaker 9: So every single every single layer has their own experts, and we want to work with We want to work with experts. They're really good at doing their own job. And we specialize in building this specialized intelligence platform, cross training inference. And we partner with all different layers to drive the best vertical solution. That's our philosophy.

Speaker 2: That makes sense. Well, congratulations. Clearly working, Jordy.

Speaker 1: Incredible progress.

Speaker 2: Thank you so much. Great see

Speaker 1: on the show. Can't wait to talk to you

Speaker 2: again soon. We'll talk to

Speaker 5: you later.

Speaker 2: Goodbye. Let me tell you about Codex. Codex is a powerful workspace for getting work done with AI agents whether you're writing code, analyzing data, creating content or automating business workflows. Codex helps you move projects forward from start to finish. There's one more news story we gotta go through really quickly. Wedding guests are now placing prop bets on everything from how long the first dance will last to whether the groom will cry during the ceremony. Call Sager and Jetty. This is a dream come true for him. Couples are using printed cards and Get this

Speaker 1: on SagerBet immediately.

Speaker 2: It's on SagerBet immediately. Printed cards and apps to let guests predict things like who gives the longest toast, how many outfits the bride wears, or whether the first kiss lasts more than six seconds. The idea is to make weddings feel more interactive, especially during slower parts of the night like cocktail hour. One app called Betting on the Wedding says more than 25,000 couples have created pools on its platform which cost $49 and includes a live leaderboard. The company says revenue is growing at triple digit run rate year over year.