Discovered Materials
Discovered Materials (legally matforge inc) is a Y Combinator-backed (Spring 2026) startup based in San Francisco building AI scientists for the semiconductor industry. The company uses swarms of AI agents to run the full materials-discovery pipeline - generating candidate materials, synthesizing them, and testing them in physical laboratories - to find novel materials for datacenters and fabrication facilities. Their stated goal is to compress a process that traditionally takes 10+ years of lab work into months, targeting 10x-better alternatives for applications such as nanoscale interconnects. Founded by Akash Ramdas (Stanford materials-science PhD/postdoc) and Advaith Sridhar (Carnegie Mellon AI, formerly Luma Labs and Persona AI). At the time of profiling the company exposes no public API, developer portal, or documentation; this entry is an enrichment lead maintained in 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 Discovered Materials 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 — Discovered Materials scores 6.8/100 (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 Discovered Materials
Each block below is one kind of artifact we hold for Discovered Materials. 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 Discovered Materials — 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.
Access & Security 1
Authentication, authorization, and security posture
Company 1
The organization behind the API
Other 1
Properties that don't map to a standard resource type
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