Eos AI
Eos AI is a San Francisco healthcare technology company building an autonomous operating system for healthcare that helps clinics and hospitals identify eligible patients and enable early care interventions. The platform connects to fragmented clinical systems (EHRs, imaging archives, labs, scheduling, and billing), resolves patient identities across sites and encounters, and links records into a continuous longitudinal history that can be searched and analyzed as one distributed database. Two harmonization products anchor the stack: VERA standardizes medical imaging across scanners, sites, and protocols to improve model performance and shorten deployment, and LUCIA structures EHR free text, ICD, SNOMED, and clinical signals into a unified representation for downstream analytics. On top of the harmonized data, Eos runs predictive models over full patient trajectories and drives automations into hospital workflows, reporting roughly 3x administrative productivity and 37% revenue recovery in early deployments. Founded in 2025 by Arya Khokhar and backed by Y Combinator (Winter 2026 batch). Its application is gated at my.helloeos.ai; no public developer API, OpenAPI, or developer portal has been published to date, so this profile captures the company identity and the security posture of its public web 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 Eos 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 — Eos AI scores 9.9/100 (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 Eos AI
Each block below is one kind of artifact we hold for Eos 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 Eos 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.
Get Started 2
Portal, sign-up, and the first successful call
Access & Security 1
Authentication, authorization, and security posture
Company 1
The organization behind the API
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