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is an AI-native materials-discovery company (Y Combinator Summer 2026) that helps research labs unlock value from unpublished and discarded experimental data.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.
Index entry only — little beyond a description and a link, and nothing machine-readable enough for an agent to act on without a human reading the site first.
API Evangelist profiles 83 Sciences the way a machine reads it — 1 machine-readable artifact, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.
Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — 83 Sciences scores 9.9/100 (minimal), with a separate agent-readiness read of 0/100 (human only). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.
Kin Score
This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.
Kin Score
How this is scored →scored 2026-07-27 · rubric v0.5
How we profile 83 Sciences
Each block below is one kind of artifact we hold for 83 Sciences. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.
Security Posture 1
Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Resources
Every other property we hold for 83 Sciences — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.
Get Started 1
Portal, sign-up, and the first successful call
Access & Security 1
Authentication, authorization, and security posture
Company 3
The organization behind the API
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