Graph AI
Graph AI is an AI-native software company (founded 2024, CEO Raghavendra Parvataraju) building Graph Safety Suite, a unified platform for pharmacovigilance and drug safety in life sciences. Powered by its agentic graphx foundation and built on Google Cloud (Vertex AI, Kubernetes), the suite unifies source intake, case processing, aggregate reporting, signal detection, risk management and regulatory compliance into one connected ecosystem via modules including /intake, /nucleus, /report, /signal, /assure and /comply. Available on Google Cloud Marketplace, the company raised a $3M seed round led by Bessemer Venture Partners in October 2025. Graph AI is in the API Evangelist network as a company profile; it publishes no public developer API, OpenAPI, SDK or documentation surface at this time.
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 Graph 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 — Graph AI scores 11.9/100 (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 Graph AI
Each block below is one kind of artifact we hold for Graph 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 Graph 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.
Access & Security 1
Authentication, authorization, and security posture
Learn 1
Tutorials, courses, talks, and written guidance
Operate 1
Status, limits, changes, and where to get help
Commercial 1
Pricing, plans, and the legal terms of use
Company 4
The organization behind the API
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