Drug Discovery AI
C

Chai Discovery

AI foundation models for molecular design, licensed as software to pharmaceutical and life sciences R&D organizations. The models predict and reprogram interactions between biochemical molecules: Chai-1 (2024) for structure prediction, Chai-2 (2025) for fully de novo antibody design, and Chai-3 (2026), which the company describes as roughly doubling the success rate of its predecessor. On Chai-2, the company reports designing all complementarity determining regions from a target and epitope prompt alone, with hit rates reported between roughly 16 and 20 percent depending on the source, against sub 0.1 percent rates the company attributes to prior methods; validation covered approximately 50 antibody targets with fewer than 20 designs tested per target. Models are reported in production at Eli Lilly, Pfizer, and Novartis, with a collaboration announced with argenx. Unlike vendors that use AI to build their own drug pipeline, Chai's product is the model itself, including custom versions trained on a customer's proprietary data.

Last VerifiedJuly 19, 2026
Founded
2024
Headquarters
San Francisco, California
Categories
drug-discovery
Indexed Products
Chai-1, Chai-2, Chai-3
Buyer Segments
Pharma / Life Sciences
Assessment

Capability Axes

AI Capability
AI Centrality
A
Vendor Published

The models are the product. Chai licenses foundation models for molecular structure prediction and de novo antibody design as software to pharmaceutical R&D organizations, including custom versions trained on a customer's proprietary data. There is no non AI version of this offering.

Autonomy and Oversight Model
Not rated
Model and Technology Transparency
A
Vendor Published

Unusually specific for this index. Named, versioned models with a public release history (Chai-1, Chai-2, Chai-3), stated task scope per model, and technical results published in preprints that describe methodology and validation design. Chai-1 was released with open weights for non commercial use. Model versioning and update practice are visible rather than inferred, which is what this axis asks for.

Clinical and Operational Evidence
B
Vendor Published

Quantified wet lab validation with stated design: approximately 50 antibody targets, fewer than 20 designs tested per target, with reported hit rates between roughly 16 and 20 percent depending on source, and reported binders for 5 of 5 miniprotein targets. Evidence is reported in preprints rather than peer reviewed journals, and the figure varies between the company's announcement and the preprint, so the record states a range. Deployment at named pharmaceutical customers is commercial validation, not clinical evidence; no candidate from these models has published clinical results.

AI Safety and PHI Stewardship
Not rated
Regulatory and Compliance
HIPAA and BAA Posture
Not rated
Security Certifications and Trust Center
Not rated
FDA and Regulatory Status
Not rated
AI Governance and Bias Disclosure
Not rated
Integration and Deployment
EHR and Interoperability Depth
Not rated
Deployment Model and Data Residency
Not rated
Commercial
Commercial Transparency
Not Rated
Vendor Published

No public pricing. Contact the vendor. Commercial terms are licensing agreements with pharmaceutical customers, in at least one case including a custom model trained on customer data; financial terms of announced agreements were not disclosed.

Setting and Specialty Coverage
A
Vendor Published

Precisely bounded and honestly stated: preclinical molecular design, principally antibodies and miniproteins, for pharmaceutical and life sciences R&D. The company does not claim clinical or downstream development capability.

Commercial

Pricing

Vendor-published figures are labeled as such. Figures labeled “Estimated” are derived from third-party sources and have not been confirmed by the vendor.

Entry Price Pricing Basis BAA Tier Implementation Source
Contact the vendor
Model licensing agreements; custom models trained on customer data Vendor Published

Model licensing agreements with pharmaceutical and life sciences organizations, in at least one announced case including early access to a next generation model and a custom model trained on the customer's proprietary data. Financial terms of announced agreements were not disclosed.

AI Health Index

An independent reference for evaluating AI vendors in healthcare. No vendor pays for inclusion, placement, or rating.

Index Status
Last index update
July 19, 2026
The AI Health Index is an editorial reference, not a regulatory body. Vendor data is verified against published sources and public regulatory filings. Figures labeled “Estimated” have not been confirmed by the vendor. See the Methodology page for evaluation standards and limitations.
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