Chai Discovery

Chai Discovery builds frontier AI to predict and reprogram the interactions between biochemical molecules. Its flagship Chai-1 is a multi-modal foundation model for biomolecular structure prediction across proteins, small molecules, DNA, RNA, glycans, and multi-component complexes, released as an open-source Python package (Apache 2.0) and as a hosted commercial server. Chai-2 extends the platform to de novo antibody design, generating novel antibodies directly from target epitopes without iterative wet-lab screening. Founded in 2023, Chai Discovery is a venture-backed digital-biology company whose developer surface centers on the chai_lab Python package, a command-line interface, and the hosted Chai Design platform.

Chai Discovery is profiled on the APIs.io network. Tagged areas include Company, Digital Biology, Structural Biology, Protein Structure Prediction, and Antibody Design.

Chai Discovery’s developer surface includes documentation, getting-started guide, support, engineering blog, signup flow, CLI, changelog, and 10 more developer resources.

🌐 Visit website 📡 Source on GitHub

25.9/100 emerging ▬ flat Agent 0/100 human only Full breakdown ↓
scored 2026-07-27 · rubric v0.5

0 APIs

CompanyDigital BiologyStructural BiologyProtein Structure PredictionAntibody DesignDrug DiscoveryMachine LearningBioinformaticsArtificial Intelligence

Kin Score

Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5

Composite quality — 25.9/100 · emerging

Contract Quality 0.0 / 25

Developer Ergonomics 9.6 / 20

Commercial Clarity 6.8 / 20

Operational Transparency 2.7 / 13

Governance 0.0 / 12

Discoverability 6.8 / 10

Agent readiness — 0/100 · human only

Machine-Readable Contract 0 / 18

Agentic Access Contract 0 / 15

MCP Server 0 / 12

Machine-Readable Auth 0 / 10

Idempotency 0 / 9

Stable Error Semantics 0 / 8

Request/Response Examples 0 / 7

Rate-Limit Signaling 0 / 7

Typed Event Surface 0 / 6

Agent Skills 0 / 5

Well-Known Catalog 0 / 4

Consent & Bot Identity 0 / 3

Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. This rating is computed from github.com/api-evangelist/chai-discovery: open an issue to ask a question, or submit a pull request to add artifacts. Want it done for you? Prioritized profiling — $2,500 →

Get Started 3

Portal, sign-up, and the first successful call

DeveloperPortal

DeveloperPortal

GettingStarted

GettingStarted

SignUp

SignUp

Documentation 1

Reference material describing how the API behaves

Documentation

Documentation

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

LLMsTxt

LLMsTxt

Build 5

SDKs, sample code, and the tooling you integrate with

SourceCode

SourceCode

GitHubOrganization

Packages

SDKs

CLI

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Operate 2

Status, limits, changes, and where to get help

Support

Support

ChangeLog

ChangeLog

Commercial 2

Pricing, plans, and the legal terms of use

TermsOfService

TermsOfService

PrivacyPolicy

PrivacyPolicy

Company 2

The organization behind the API

Website

Website

Blog

Blog

Source (apis.yml)

aid: chai-discovery
name: Chai Discovery
description: Chai Discovery builds frontier AI to predict and reprogram the interactions between biochemical molecules. Its
  flagship Chai-1 is a multi-modal foundation model for biomolecular structure prediction across proteins, small molecules,
  DNA, RNA, glycans, and multi-component complexes, released as an open-source Python package (Apache 2.0) and as a hosted
  commercial server. Chai-2 extends the platform to de novo antibody design, generating novel antibodies directly from target
  epitopes without iterative wet-lab screening. Founded in 2023, Chai Discovery is a venture-backed digital-biology company
  whose developer surface centers on the chai_lab Python package, a command-line interface, and the hosted Chai Design platform.
url: https://raw.githubusercontent.com/api-evangelist/chai-discovery/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- amplify-partners
- bain-capital-ventures
- dcvc
- general-catalyst
- index-ventures
- menlo-ventures
- sapphire-ventures
x-tier: stub
x-tier-reason: portfolio-lead
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source: []
  generated: '2026-07-22'
  method: derived
specificationVersion: '0.20'
created: '2026-07-17'
modified: '2026-07-18'
image: https://framerusercontent.com/images/GJGIRhiMoAIv0hl9KDGSIa5FCEw.png
tags:
- Company
- Digital Biology
- Structural Biology
- Protein Structure Prediction
- Antibody Design
- Drug Discovery
- Machine Learning
- Bioinformatics
- Artificial Intelligence
apis: []
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Website
  url: https://chaidiscovery.com
- type: DeveloperPortal
  url: https://lab.chaidiscovery.com
- type: Documentation
  url: https://docs.chaidiscovery.com
- type: GettingStarted
  url: https://github.com/chaidiscovery/chai-lab#running-the-model
- type: SourceCode
  url: https://github.com/chaidiscovery/chai-lab
- type: GitHubOrganization
  url: https://github.com/chaidiscovery
- type: Support
  url: https://github.com/chaidiscovery/chai-lab/discussions
- type: Blog
  url: https://www.chaidiscovery.com/news
- type: SignUp
  url: https://lab.chaidiscovery.com
- type: TermsOfService
  url: https://www.chaidiscovery.com/terms-of-service
- type: PrivacyPolicy
  url: https://www.chaidiscovery.com/privacy-policy
- type: Packages
  url: packages/chai-discovery-packages.yml
- type: SDKs
  url: packages/chai-discovery-packages.yml
- type: CLI
  url: cli/chai-discovery-cli.yml
- type: ChangeLog
  url: changelog/chai-discovery-changelog.yml
- type: LLMsTxt
  url: llms/chai-discovery-llms.txt
- type: DomainSecurity
  url: security/chai-discovery-domain-security.yml
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence