Menlo Ventures

Been tracking and meeting Lin Qiao since the Series A with my partner Tim Tully. Excited to finally be partnering up with Fireworks AI! They have nailed the intersection of custom models, frontier intelligence, and lowest most efficient token delivery. The growth is astonishing, and they are playing an important role in the multi model ecosystem. We are investing in complementary companies driving and broadening the token economy incl Fireworks, OpenRouter, Modal, Gimlet Labs... and more to come soon!

I'm excited to announce our $1.5 billion Series D at a $17.5 billion valuation, led by Atreides Management, Index Ventures, and TCV, with participation from Evantic Capital, Lightspeed Venture Partners, NVIDIA, 20VC, Bessemer Venture Partners, Menlo Ventures, and others. We have crossed $1 billion in annualized revenue run rate (up 5x YoY) and now serve more than 40 trillion tokens per day (up 8x YoY). That growth is coming from one clear shift: General intelligence will be abundant. Specialized intelligence will be the moat. Fireworks builds a specialized intelligence platform that makes it accessible to every company. More than 95% of the tokens Fireworks serves today come from models specialized on customers’ proprietary data and trained for a specific job. These aren't demos or experiments. They're production systems running every day across coding, legal, commerce, transportation, finance, sales, recruiting, hospitality, design, and beyond. This is the transition Fireworks was built for. Before foundation models, all AI was specialized. Foundation models changed the starting point, which makes specialization lighter, faster, and much more accessible. It also makes it more important. When everyone can start from a strong base model, advantage comes from how quickly a company can turn that model into something specific to its product and market. We see this every day at Fireworks across bleeding-edge AI startups like Cursor, Cognition, Harvey, Glean, and Lovable to industry leaders and enterprises like Revolut, Airwallex, Unity, Uber, and Shopify. Across our customer base, the pattern is the same: the strongest AI products are not built on generic models. They are built on intelligence shaped by proprietary data, real usage, and domain-specific definitions of quality. That requires purpose-built infrastructure. Training and inference cannot be separate systems stitched together after the fact. They have to be co-designed and co-optimized to deliver the highest computational efficiency, scaling across massively distributed compute resources globally rather than being limited by a single centralized architecture, usually at very high cost. Companies need to adapt models, serve them at scale, measure performance in production, and continuously improve them with real-world data. That's where specialized intelligence compounds. The best companies have never been generalists. They win by becoming exceptionally good at something specific and building knowledge, judgment, and systems that define the reason to exist. Our Series D gives us the resources to help many more companies do the same. This is still day one. Every company will own its intelligence. Come build a specialized intelligence platform with us - we're hiring passionate researchers, engineers, and GTM operators.

Today, we're thrilled to announce our $15m Series A, led by our friends at Chemistry, with participation from Menlo Ventures. AI has broken software development. Agents are writing code faster than ever, but review and testing haven't kept pace. Engineering teams are drowning in longer review cycles and more bugs than ever. The bottleneck isn't writing code anymore, it's knowing whether to trust it. Every codebase has thousands of flows, edge cases, and dependencies. Testing all of them would consume enormous resources - so teams make a tradeoff: these flows are worth testing, these aren't. Ship fast, and hope nothing breaks in the rest. We don't think that tradeoffs should exist. And with agents now writing 10x the code volume, it can’t. Meticulous tests every flow, edge case and permutation - automatically. We watch how developers and agents actually use the product, turn those sessions into thousands of tests, and show developers the full impact of their code change, in minutes. We’re grateful to be working with the world’s top AI-driven teams including Notion, ElevenLabs, Dropbox, Wiz, Mercor and LaunchDarkly, who depend on us to verify their changes before every merge. We’re also grateful to be backed by an incredible group of angels: Lachy Groom (formerly Stripe), Jason Warner (Poolside), Arash Ferdowsi (Dropbox), Scott Belsky (formerly Adobe), Guillermo Rauch (Vercel), Calvin French-Owen (Segment, formerly OpenAI), Caitlin Colgrove (Hex), and Jason Ginsberg (formerly head of engineering at Cursor, now xAI). As AI agents write more of the world's code, the gap between shipping fast and shipping safely will only widen. We built Meticulous so you can ship fast, without breaking things - and we're just getting started 🚀

Congrats to Joshua Meier, Jack Dent, Matthew McPartlon, Jacques Boitreaud and the whole Chai Discovery team on Series C and for continuing to push the frontier of AI in drug discovery toward deployment at scale! Excited to continue to collaborate! Menlo Ventures