OpenAI-backed Chai Discovery raises $130m series B for research

Chai Discovery has raised US$130 million in a series B round co-led by Oak HC/FT and General Catalyst, valuing the company at US$1.3 billion.

The San Francisco-based company uses AI to model and design biochemical molecules, aiming to improve drug discovery processes.

New investors Emerson Collective and Glade Brook joined existing backers such as Thrive Capital, Menlo Ventures, and OpenAI in the round.

Chai Discovery said the new funding will go toward research, product development, and expanding commercialization.

The company previously announced a US$70 million series A earlier this year.

The company’s total funding now exceeds US$225 million.

Oak HC/FT’s Annie Lamont and General Catalyst’s Hemant Taneja will join Chai Discovery’s board as part of the deal.

🔗 Source: Chai Discovery

🧠 Food for thought

Implications, context, and why it matters.

Chai-2, a second-generation AI model for antibody design, hit roughly 16–20% in wet-lab validations (physical lab experiments) across 52 novel targets (disease-relevant proteins) with no known binders (molecules that attach to a target) 1. It produced functional antibodies with nanomolar-range affinities (very strong binding) in under two weeks, while traditional methods post under 0.1% 1.
Timelines fell from months to days through zero-shot generation (producing designs without target-specific training examples) 2. Only target protein and epitope (the protein’s binding site) inputs are needed, which removes iterative screening cycles 2.
Chai’s multimodal architecture blends sequence, structure, and function data 2. It optimizes binding and stability along with specificity plus developability (how manufacturable a molecule is with stability plus safety) in a single forward pass (one evaluation through the model) 2. That reduces failure modes that usually need sequential optimization 2.
Chai-1, the prior model, is free for academic and commercial use via a web interface 3. That brings in revenue from commercial licensing agreements and pharmaceutical partnerships 3.

Chai Discovery has $130 million for R&D (research and development) plus commercialization 4. It plans to expand infrastructure for computationally intensive multimodal modeling and structure-aware generative design (models that account for 3D geometry) 4.
Open roles include computer science and engineering in San Francisco 5. Biology, chemistry, and physics are hiring needs 5. Vendors of high-performance GPUs, molecular simulation platforms, plus wet-lab services should move early 2 5. Cloud compute, Machine Learning Operations (MLOps) tooling, and lab automation buys look imminent as the pipeline grows beyond 52 validated targets 2 5.