Iris.ai
Iris.ai is a Norwegian AI company providing an AI knowledge foundation for regulated enterprises, turning complex enterprise and scientific data into trustworthy, compliant AI. Its platform spans three products — Axion (data organization for AI-ready intelligence), Neuralith (enterprise knowledge integration into AI engines), and RSpace, the Researcher Workspace that lets R&D teams, librarians, and academics search, filter, analyze, extract, summarize, and report across scientific literature. Iris.ai is backed by 500 Global. The company does not currently publish a public developer API, SDKs, or a developer portal; this profile captures its public identity and domain-security posture pending any future developer 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 Iris.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 — Iris.ai scores 12.3/100 (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 Iris.ai
Each block below is one kind of artifact we hold for Iris.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 Iris.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
Operate 2
Status, limits, changes, and where to get help
Commercial 2
Pricing, plans, and the legal terms of use
Company 2
The organization behind the API
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