DeepCell
Deepcell is a Menlo Park, California life-sciences company building an AI-powered platform for label-free single-cell morphology analysis, a field it calls morpholomics. Its REM-I platform combines label-free imaging, deep learning, and gentle cell enrichment to treat single-cell morphology as a high-dimensional, quantitative biological readout without destructive sample preparation. Applications span oncology and tumor heterogeneity profiling, phenotypic drug discovery, cell and gene therapy quality control and manufacturing, regenerative medicine, transplant monitoring, neurobiology, and agriculture. Backed by a16z and DCVC, Deepcell was added to the API Evangelist network as a portfolio lead; it currently publishes a corporate site, blog, and publications but no public developer API, SDK, or documentation surface.
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 DeepCell 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 — DeepCell scores 8.1/100 (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 DeepCell
Each block below is one kind of artifact we hold for DeepCell. 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 DeepCell — 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 2
The organization behind the API
← All providers · Data indexed from github.com/api-evangelist/deepcell · machine-readable index on apis.io