Chai Discovery Raises $70 Million Series A Led by Menlo Ventures to Advance AI-Driven Antibody Design Platform
Chai Discovery, a San Francisco-based biotech startup founded in 2024, has secured US $70 million in a Series A funding round led by Menlo Ventures via its Anthology Fund, which it operates in partnership with Anthropic. The round brings the company’s total funding to approximately US $100 million.
The investment includes participation from a wide range of new and existing backers: new investors such as Yosemite, DST Global Partners, SV Angel, Avenir, and DCVC; as well as existing supporters including Thrive Capital, OpenAI, Dimension Capital, Neo VC, Lachy Groom, and Fred Ehrsam.
Chai Discovery’s core innovation lies in its AI-driven molecular-design platform, powered by its proprietary model Chai-2, which the company says is capable of generating novel antibodies with hit-rates of 16–20 percent—orders of magnitude higher than traditional computational methods, which typically achieve hit-rates below 1 percent. The company emphasizes that its generative AI enables “de novo antibody and binder design” without relying on pre-existing templates or sequence libraries, marking a major departure from conventional drug-discovery processes.
The fresh capital will be used to expand Chai’s model capabilities, accelerate target exploration across multiple therapeutic areas, and establish strategic partnerships with leading pharmaceutical companies. The company also plans to expand its lab operations and scale experimental validation pipelines to ensure rapid iteration between digital models and wet-lab data.
Chai Discovery was founded by Joshua Meier, formerly of Absci, Facebook AI, and OpenAI; Jack Dent, a former Stripe engineer; and AI researchers Matthew McPartlon and Jacques Boitreaud. The startup recently added Mikael Dolsten, the former Chief Scientific Officer at Pfizer, to its board of directors, further deepening its pharmaceutical expertise and signaling its commitment to bridging advanced AI research with real-world drug development.
According to investors, Chai Discovery represents a new wave of biotech companies applying foundation-model techniques to molecular biology. Menlo Ventures Partner Greg Yap said that Chai’s work could “reshape how we design therapeutics from first principles,” emphasizing that its foundation-model approach for biology offers scalability similar to what large language models achieved in software. Meanwhile, participation from OpenAI underscores a broader trend of AI companies extending their reach into scientific domains beyond natural language and image generation.
The company’s near-term focus is to translate its high in-silico hit rates into validated therapeutic leads and demonstrate pre-clinical efficacy. Its platform aims to shorten the time from target selection to lead molecule discovery from months or years to mere weeks—potentially reducing R&D costs by up to 90 percent. Chai Discovery also aims to leverage partnerships to move several internally generated antibodies toward clinical testing within the next two years.
As the biotech industry increasingly embraces AI-enabled discovery pipelines, Chai Discovery stands out for its focus on generalizable molecular design rather than narrow target optimization. Its long-term vision is to build an “AI laboratory for biology” capable of designing antibodies, enzymes, and binders with precision and reproducibility akin to software engineering.
While the company’s rapid rise has captured strong investor enthusiasm, it faces familiar challenges in bridging computational discovery and clinical validation. Demonstrating consistent wet-lab success, scaling infrastructure, navigating regulatory frameworks, and building pharmaceutical partnerships will be crucial as it transitions from a research-stage AI lab to a commercially viable biotech innovator.
With US $70 million in Series A funding and backing from top-tier venture firms in both AI and life sciences, Chai Discovery now stands among the most well-funded generative-biology startups of 2025, positioning itself to accelerate the convergence of artificial intelligence and therapeutic discovery.
