83 Sciences website screenshot

83 Sciences

83 Sciences is an AI-native materials-discovery company (Y Combinator Summer 2026) that helps research labs unlock value from unpublished and discarded experimental data. Roughly 90% of experimental data never reaches publication; 83 Sciences works on-site with researchers to capture and structure that hidden data into a queryable database, then applies AI-powered analysis and generative models to learn from a lab's full experimental history — including failed experiments — to surface novel materials, co-authored manuscripts, and patents. Founded by researchers from MIT, Stanford, Harvard, and Columbia and based in San Francisco. The company currently ships no public API or developer surface; this profile tracks its identity for the API Evangelist network.

83 Sciences is profiled on the APIs.io network. Tagged areas include Company, Materials Science, Artificial Intelligence, Research Data, and Scientific Discovery.

🌐 Visit website 📡 Source on GitHub
9.9/100 minimal ▬ flat Agent 0/100 human only Full breakdown ↓
scored 2026-07-27 · rubric v0.5
0 APIs
CompanyMaterials ScienceArtificial IntelligenceResearch DataScientific DiscoveryLife SciencesMachine Learning

Kin Score

Kin Score Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5
Composite quality — 9.9/100 · minimal
Contract Quality 0.0 / 25
Developer Ergonomics 0.0 / 20
Commercial Clarity 2.6 / 20
Operational Transparency 0.0 / 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/83-sciences: open an issue to ask a question, or submit a pull request to add artifacts. Want it done for you? Prioritized profiling — $2,500 →

Security Posture 1

Authentication, domain security, vulnerability disclosure, and trust-center signals.

83 Sciences Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Resources

Get Started 1

Portal, sign-up, and the first successful call

Login
Login

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity
DomainSecurity

Company 3

The organization behind the API

Website
Website
 LinkedIn
LinkedIn
 Twitter
Twitter

Source (apis.yml)

apis.yml Raw ↑ 
aid: 83-sciences
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source: []
  generated: '2026-07-22'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/83-sciences.png
name: 83 Sciences
description: 83 Sciences is an AI-native materials-discovery company (Y Combinator Summer 2026) that helps research labs unlock
  value from unpublished and discarded experimental data. Roughly 90% of experimental data never reaches publication; 83 Sciences
  works on-site with researchers to capture and structure that hidden data into a queryable database, then applies AI-powered
  analysis and generative models to learn from a lab's full experimental history — including failed experiments — to surface
  novel materials, co-authored manuscripts, and patents. Founded by researchers from MIT, Stanford, Harvard, and Columbia
  and based in San Francisco. The company currently ships no public API or developer surface; this profile tracks its identity
  for the API Evangelist network.
url: https://raw.githubusercontent.com/api-evangelist/83-sciences/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- y-combinator
x-tier: stub
x-tier-reason: portfolio-lead
specificationVersion: '0.20'
created: '2026-07-17'
modified: '2026-07-17'
tags:
- Company
- Materials Science
- Artificial Intelligence
- Research Data
- Scientific Discovery
- Life Sciences
- Machine Learning
apis: []
common:
- type: DomainSecurity
  url: security/83-sciences-domain-security.yml
- type: Website
  url: https://83sciences.ai
- type: Login
  url: https://platform.83sciences.ai/
- type: LinkedIn
  url: https://www.linkedin.com/company/83sciences.ai
- type: Twitter
  url: https://x.com/83sciences
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence