Mendel AI
Mendel AI is a San Jose, California clinical AI company founded in 2017 by Dr. Karim Galil to streamline oncology research by organizing real-world data and accelerating clinical-trial workflows. Its flagship platform, Mendel Hypercube, pairs large language models with a clinician-built clinical knowledge hypergraph to add physician-like reasoning to LLMs operating over electronic health records, pathology reports, genomic data, clinician notes, claims, diagnostic data, and EDC submissions. Hypercube is offered as three productized experiences — Hypercube Cohort for patient cohort discovery (with funnel-style criteria analysis and direct integration to clinicaltrials.gov), Hypercube Analyst for AI-driven analysis of structured and unstructured real-world data, and Build Your Own Hypercube for custom clinical-data queries. The platform integrates with enterprise data warehouses (Databricks, Snowflake) and BI tools (Tableau, Qlik), and is available through the AWS Marketplace, Microsoft Azure Marketplace, and natively on the Snowflake AI Data Cloud. Mendel serves pharma, providers, payers, and research organizations including Quest Diagnostics, Boston Scientific, Gatehouse Bio, and the University of Pennsylvania, with published evidence in oncology trial prescreening. Mendel has no public developer portal, OpenAPI specification, SDK, or open-source GitHub repositories; integration is delivered through enterprise contracts and cloud-marketplace deployments.
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 Mendel AI 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 — Mendel AI scores 8.6/100 (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 Mendel AI
Each block below is one kind of artifact we hold for Mendel AI. 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 Mendel AI — 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.
Build 1
SDKs, sample code, and the tooling you integrate with
Access & Security 1
Authentication, authorization, and security posture
Company 3
The organization behind the API
Other 8
Properties that don't map to a standard resource type
Scroll within the panel for all 8 ·
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