Chai Discovery vs Cradle (2026)
Both license AI for protein design to research teams rather than building their own pipelines, and they do different jobs. Chai Discovery designs antibodies and miniproteins from scratch: a customer names the target, the epitope and the format, and Chai-2, or Chai-3 from 2026, proposes binders. Its first model, Chai-1, was released with open weights. Cradle optimizes proteins a team already has. Scientists upload results from each screening round, and Cradle fine tunes a project model on public data, its own wet lab data and the customer's results, then proposes sequences and whole experimental plates balancing activity, binding, stability and expression. Chai is for starting from a target; Cradle is for improving a molecule over rounds of experiments in your own lab.
- De novo design of antibodies and miniproteins from a target and epitope, including monoclonal and VHH formats.
- Published results per target class with counts, and an open weights structure model, Chai-1.
- Design for agonism or antagonism against a particular antigen state.
- Optimization across rounds, with a model fine tuned on each customer's own assay results.
- Complete experimental plates proposed, balancing several properties at once.
- A web interface and an API covering antibodies, enzymes, peptides and vaccine antigens, backed by Cradle's own wet lab in Amsterdam.
This comparison is published by AI Health Index, an independent research platform that compares healthcare AI vendors objectively. Chai Discovery and Cradle are each graded against the same capability taxonomy, from each vendor's own public materials and the regulatory record, under the AI Health Index verification standard. No vendor pays for placement, and no vendor has reviewed this page. How this evidence is graded
Plain facts
| Fact | Chai Discovery | Cradle |
|---|---|---|
| Primary category | Drug Discovery AI | Drug Discovery AI |
| Founded | 2024 | 2022 |
| Headquarters | San Francisco, California | Amsterdam, Netherlands |
| Website | chaidiscovery.com | cradle.bio |
Side by Side
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Product updates
The latest logged changes from each vendor, newest first, each linked to its source.
Chai Discovery
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Model / architecture
Chai Discovery deployed Chai-3, a next generation antibody design model that the company describes as roughly doubling the success rate of Chai-2 and binding more tightly to harder targets.
Source
Each vendor in one paragraph
Written to be quoted whole. Each paragraph opens the AI Health Index profile of the vendor: what the product is, who buys it and what it does.
San Francisco company that licenses foundation models for molecular design to pharmaceutical and life sciences research organizations, rather than using them to build its own pipeline. Three generations are published: Chai-1 (2024) for biomolecular structure prediction, released with open weights under a community license; Chai-2 (2025) for de novo design of antibodies and miniproteins from a target and epitope prompt; and Chai-3 (2026), which the company describes as roughly doubling its predecessor's success rate.
Source: AI Health Index, September 2026
Protein engineering software company, based in Amsterdam and Zurich, that licenses an AI platform directly to R&D teams rather than working through discovery partnerships. Scientists upload assay results from screening or optimization rounds, and the platform fine tunes a project specific model on public protein data, Cradle's own wet lab data and the customer's results, then proposes candidate sequences and complete experimental plates that balance several properties at once, such as activity, binding, stability and expression.
Source: AI Health Index, September 2026
Questions buyers ask
How do Chai Discovery and Cradle work with the EHR?
For Chai Discovery, the design models are reached through access granted on application, the inputs are a structure or a sequence supplied by the customer, and the one openly distributed model is downloaded and run by the customer itself.
The platform page describes integration in general terms: full API access to connect Cradle to existing pipelines and automate workflows, custom data schemas matching lab workflows through the interface and the API, and, in beta, the customer's own internally developed predictors running inside Cradle. From the AI Health Index, drawn from each vendor's own published materials and the regulatory record, verified September 28, 2026. No vendor pays for placement.
How do Chai Discovery and Cradle handle patient data?
Chai's privacy policy (last updated 30 June 2025) covers personal information collected through the website and the company's online offerings, with retention stated as a principle rather than a schedule, and its acceptable use policy prohibits using the models to violate anyone's privacy rights.
For Cradle, the home page repeats that customer data is never used to train models for others. From the AI Health Index, drawn from each vendor's own published materials and the regulatory record, verified September 28, 2026. No vendor pays for placement.
Which settings and specialties do Chai Discovery and Cradle cover?
With Chai Discovery, the company does not claim clinical or downstream development capability. Testing runs across the classes it names: 28 target antigens in the developability work, six G protein coupled receptors, a class the company notes is hard for screening methods, and three peptide MHC complexes, each with the number of designs tested reported.
Cradle says its approach works "across modalities and data types" and that "if you can measure it, Cradle can help you optimize it", for pharma, industrial biotechnology, food technology and beyond, and names four modalities: antibodies, enzymes, peptides and vaccines. From the AI Health Index, drawn from each vendor's own published materials and the regulatory record, verified September 28, 2026. No vendor pays for placement.
What evidence is published for Chai Discovery and Cradle?
For Chai Discovery, the product page states double digit success rates for antibodies and above 50 percent for miniproteins, and characterization within two weeks without high throughput screening.
Cradle also took part in the Align to Innovate Protein Engineering Tournament, whose organizers have published its results as a paper; Cradle's account of its enzyme results is on its own blog. From the AI Health Index, drawn from each vendor's own published materials and the regulatory record, verified September 28, 2026. No vendor pays for placement.
Related comparisons
Other published head to head assessments involving these vendors or their closest peers.
Both records were reviewed on this site in September 2026. Neither publishes a price.
Ask both how their models handle designs far from anything in the training data, and what they tell you when a prediction should not be trusted.