310.ai is a technology company.
310.ai is a technology company.
310.ai has raised $4.0M across 1 funding round.
310.ai has raised $4.0M in total across 1 funding round.
310.ai has raised $4.0M in total across 1 funding round.
310.ai's investors include Alumni Ventures, Canaan Partners, Cota Capital, Matt Ocko, Modern Venture Partners, NightDragon, Parkway VC, Spark Capital, Catherine Lu, Thomas Tull.
310.ai is a technology company developing generative AI for molecular programming in life sciences, specifically building an AI operating system and foundational models to enable programmable biology. Their core product, the Molecule Programming Model (MPM4), generates novel protein sequences from text descriptions, addressing the design of novel biomolecules—a breakthrough poised to transform biology research and applications.[1][2][4] Targeting scientists, researchers, and biotechs, 310.ai solves the challenge of engineering proteins beyond nature's 4 billion years of evolution by leveraging GPUs for rapid, programmable generation, making biology more accessible for real-world problems like therapeutics in immunology, cancer, and cardiometabolic areas.[1][2][3]
The company has assembled a team from top institutions, including former roles at Facebook, Amgen, and Stanford, with early momentum from pioneering text-to-protein generation and partnerships like AMD Instinct accelerators.[1][4]
310.ai emerged from the belief that generative AI and biology's convergence represents a historic inflection point, prompting founders and team members to leave leading research institutions, tech companies, and biotechs.[1] Key founders include Koosh, a serial entrepreneur and former Staff AI Engineer at Facebook, where he led Ads Ranking; he previously founded Concertboom (a top event ticket search engine) and Kookoo.ai (an AI for abstract paintings), with early academic acclaim via an Erdos number of 2 in cryptography.[1] The other highlighted founder holds a Stanford Ph.D. and postdoc in computational protein design under David Baker, with Amgen experience in structure prediction, protein engineering for therapeutics, and launching the AmgenFold platform; she is a multiple patent holder published in *Science*, *PNAS*, and *eLife*.[1]
The idea crystallized around compressing nature's evolutionary timeline using AI, with pivotal early traction in developing the MP model for text-to-protein generation.[1][2]
310.ai rides the generative AI + biology trend, where models like theirs enable "programmable biology" by generating functional proteins on demand, a convergence amplified by advances in compute like GPUs and accelerators.[1][2][4] Timing is critical amid post-AlphaFold structure prediction breakthroughs, shifting focus to sequence generation for novel therapeutics—market forces like rising demand for AI-driven drug discovery (e.g., immunology, oncology) favor them, with biomolecule design flagged as AI's top decade-defining impact.[3] They influence the ecosystem by democratizing biology, empowering biotechs to iterate faster and solve unmet needs, potentially accelerating programmable matter in healthtech.[1][3]
Next for 310.ai involves scaling MPM4 and successors for broader applications, like custom therapeutics or synthetic biology tools, fueled by GPU advancements and ecosystem partnerships.[4] Trends like multimodal AI-bio integration and compute democratization will shape their path, evolving their influence from niche protein engineering to foundational infrastructure for life sciences. As pioneers in text-to-protein, they stand to redefine biology's programmability, echoing their origins in betting big on this inflection point.[1][2]
310.ai has raised $4.0M across 1 funding round. Most recently, it raised $4.0M Seed in December 2022.
| Date | Round | Lead Investors | Other Investors |
|---|---|---|---|
| Dec 1, 2022 | $4.0M Seed | Alumni Ventures, Canaan Partners, Cota Capital, Matt Ocko, Modern Venture Partners, NightDragon, Parkway VC, Spark Capital, Catherine Lu, Thomas Tull |