Eos AI website screenshot

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.

Eos AI is profiled on the APIs.io network. Tagged areas include Company, Health, Healthcare, AI, and Machine Learning.

🌐 Visit website 📡 Source on GitHub
9.9/100 minimal ▬ flat Agent 0/100 human only Full breakdown ↓
scored 2026-07-27 · rubric v0.5
0 APIs
CompanyHealthHealthcareAIMachine LearningClinical DataData HarmonizationMedical ImagingPredictive AnalyticsHospital Operations

Kin Score

Kin Score Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5
Composite quality — 9.9/100 · minimal
Contract Quality 0.0 / 25
Developer Ergonomics 0.0 / 20
Commercial Clarity 2.6 / 20
Operational Transparency 0.0 / 13
Governance 0.0 / 12
Discoverability 6.8 / 10
Agent readiness — 0/100 · human only
Machine-Readable Contract 0 / 18
Agentic Access Contract 0 / 15
MCP Server 0 / 12
Machine-Readable Auth 0 / 10
Idempotency 0 / 9
Stable Error Semantics 0 / 8
Request/Response Examples 0 / 7
Rate-Limit Signaling 0 / 7
Typed Event Surface 0 / 6
Agent Skills 0 / 5
Well-Known Catalog 0 / 4
Consent & Bot Identity 0 / 3
Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. This rating is computed from github.com/api-evangelist/eos-ai: open an issue to ask a question, or submit a pull request to add artifacts. Want it done for you? Prioritized profiling — $2,500 →

Security Posture 1

Authentication, domain security, vulnerability disclosure, and trust-center signals.

Eos Ai Domain Security

TLSv1.3 · DMARC

SECURITY

Resources

Get Started 2

Portal, sign-up, and the first successful call

Login
Login
 Demo
Demo

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity
DomainSecurity

Company 1

The organization behind the API

Website
Website

Source (apis.yml)

apis.yml Raw ↑ 
aid: eos-ai
name: Eos AI
description: '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.'
url: https://raw.githubusercontent.com/api-evangelist/eos-ai/refs/heads/main/apis.yml
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source: []
  generated: '2026-07-22'
  method: derived
image: https://www.helloeos.ai/static/images/favicon.png
x-type: company
x-source: vc-portfolio
x-backed-by:
- y-combinator
x-tier: stub
x-tier-reason: portfolio-lead
specificationVersion: '0.20'
created: '2026-07-17'
modified: '2026-07-19'
tags:
- Company
- Health
- Healthcare
- AI
- Machine Learning
- Clinical Data
- Data Harmonization
- Medical Imaging
- Predictive Analytics
- Hospital Operations
apis: []
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: DomainSecurity
  url: security/eos-ai-domain-security.yml
- type: Website
  url: https://www.helloeos.ai/
- type: Login
  url: https://my.helloeos.ai/login
- type: Demo
  url: https://calendly.com/arya-helloeos/30min
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence