# 83 Sciences

**Canonical:** https://apis.io/providers/83-sciences/  
**Website:** https://83sciences.ai  
**APIs profiled:** 0

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is an AI-native materials-discovery company (Y Combinator Summer 2026) that helps research labs unlock value from unpublished and discarded experimental data.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.

## Kin Score — 4.6 / 100 (minimal)

Scored 2026-08-20 under rubric 0.12.0. Trend: flat (+0.0 from 4.6).

| Facet | Score |
|---|---|
| Discoverability | 50.0 |
| Contract Quality | 0.0 |
| Governance | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 0.0 |
| Developer Ergonomics | 0.0 |
| Commercial Clarity | 6.6 |
| Access Clarity | 6.6 |

Regulatory layer — **Health**: 7.5 (matched via tags).

## Agent readiness — 0.0 (human-only)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | no |
| Reversibility Documented | no |
| MCP Server | no |
| Auth Clarity | no |
| Idempotency | no |
| Error Semantics | no |
| OpenAPI Examples | no |
| Rate Limit Signal | no |
| Event Surface Described | no |
| Agent Skills | no |
| Well Known Catalog | no |
| Consent Identity | no |
| Agent Card | no |
| Dry Run Mode | no |

## Access

Unknown — onboarding: unknown, pricing: unknown, trial: no (confidence: low).

## Security (1)

- **83 Sciences Domain Security** — TLSv1.3 · HSTS · DMARC

## Tags

Company, Materials Science, Artificial Intelligence, Research Data, Scientific Discovery, Life Sciences, Machine-Learning

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Profiled by [API Evangelist](https://apievangelist.com) and published on [APIs.io](https://apis.io/providers/83-sciences/). Scores are computed from the provider's own public artifacts under a published rubric.