Chai Discovery, a biotech company based in San Francisco, had secured $130 million in fresh capital at a $1.3 billion valuation. This comes months after its previous raise, wherein it raised $70 million, bringing total funding to $225 million. Backers include Oak HC/FT and General Catalyst, alongside Thrive Capital, Menlo Ventures and OpenAI.
The capital will be used to build a computer-aided design suite for molecules, positioning Chai as an infrastructure player rather than a single-asset biotech.
A team built for science and scale
Chai was founded in 2024 by a group whose experience cuts across research and product execution. CEO Joshua Meier previously worked at Absci, Meta AI and OpenAI, while Jack Dent brings large-scale engineering and product leadership from Stripe. Co-founders Matthew McPartlon and Jacques Boitreaud add deep research credentials in machine learning and molecular science.
The company’s scientific ambitions are reinforced by the addition of Mikael Dolsten to its board. As former chief scientific officer at Pfizer, Dolsten oversaw the progression of 150 molecules into clinical trials and the approval of 36 medicines. His presence bridges a crucial gap between computational design and real-world drug development, offering insight into what it takes to move candidates from models into patients.
From prediction to invention models
Chai first drew attention with Chai-1, an open-source model released in 2024 that improved how researchers predict molecular structures and interactions. By making these capabilities widely available, the company established credibility and built a community around its approach.
Chai-2 marks a decisive step forward. Rather than analysing existing molecules, the system can design antibodies from scratch. Given only a target antigen and epitope, it generates new antibodies engineered to bind with precision. The reported hit rate, approaching 20%, represents a sharp jump from traditional lab screening, where researchers often sift through millions of candidates to find a single promising one. Even earlier computational methods rarely crossed 0.1%.
Targets the hardest diseases
This leap in efficiency changes what is economically and scientifically feasible. Chai-2 opens the door to tackling targets that have resisted conventional approaches, including complex viral structures, cancer-related proteins and other elusive disease drivers. By removing dependence on existing antibody templates, researchers can explore entirely new therapeutic spaces.
With fresh capital in hand, Chai now faces the challenge of turning computational breakthroughs into medicines that matter. If it succeeds, its design suite could become a standard tool for drug developers, reshaping how treatments are conceived long before they reach the lab bench.
“Looking back over the last five to 10 years, there’s been so much hype on AI for drug discovery,” co-founder and Chief Executive Officer Josh Meier said. “This is the year things started working.”
“Nowhere is AI transformation more needed than in drug development,” Oak HC/FT managing partner and co-founder Annie Lamont said in a statement. “It can take over a decade and cost upwards of a billion dollars to bring a medicine from bench to bedside. The Chai Discovery team is rewriting that story.”
“If 2025 has been the year of research, 2026 will be the year of deployment and pharmaceuticals baking this into the everyday workflow,” co-founder and President Jack Dent said.
