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Us2.ai

Us2.ai is a Singapore-founded medical AI company (founded 2017 as eko.ai by James Hare, Dr. Carolyn Lam, and Dr. Yoran Hummel) whose FDA-cleared, CE-marked software fully automates echocardiography analysis — taking a routine DICOM echo study and returning a complete structured report with measurements, disease detection (heart failure, cardiac amyloidosis, aortic stenosis, pulmonary hypertension, strain), and findings in seconds, with zero clicks. The platform is vendor-neutral and DICOM-native, deploying via ultrasound OEMs (Fujifilm LISENDO 880), AI marketplaces (Viz.ai, Harrison.ai), cardiology PACS (Merge Cardio via DICOM-SR/HL7), or as a cloud-hosted service with an API for programmatic study submission and result retrieval used by research programs, imaging core labs, and pharma trials (partner-gated; no public API reference is published). Validated in 150+ peer-reviewed publications, cleared in 28+ regulatory markets, and ISO 13485 / ISO 27001:2022, SOC 2 Type II, MDSAP, HIPAA, and GDPR compliant. Backed by Partech, Sequoia India, EDBI, and IHH Healthcare.

human only

More than an index entry, but the surface is still mostly links rather than artifacts — the cohort most likely to move a full band from modest, well-targeted work.

Kin Score

API Evangelist profiles Us2.ai the way a machine reads it — 3 machine-readable artifacts, 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 — Us2.ai scores 28.3/100 (emerging), 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 Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5
Composite quality — 28.3/100 · emerging
Contract Quality 0.0 / 25
Developer Ergonomics 3.0 / 20
Commercial Clarity 10.0 / 20
Operational Transparency 2.1 / 13
Governance 0.0 / 12
Discoverability 6.8 / 10
Regulatory · Health 9.8 / 15
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

How we profile Us2.ai

Each block below is one kind of artifact we hold for Us2.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 3

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.

Us2Ai Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Us2Ai Vulnerability Disclosure

Hackerone · contact published

SECURITY

Us2Ai Trust Center

SOC 2 Type II, ISO 27001:2022, ISO 13485, MDSAP, HIPAA, GDPR, NHS DSPT, NHS DTAC

SECURITY

Resources

Every other property we hold for Us2.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 1

Portal, sign-up, and the first successful call

Documentation 1

Reference material describing how the API behaves

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

Design & Contract 1

Pagination, idempotency, versioning, errors, and events

Build 1

SDKs, sample code, and the tooling you integrate with

Operate 1

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

← All providers · Data indexed from github.com/api-evangelist/us2ai · machine-readable index on apis.io