Qure.ai

Qure.ai is a healthcare artificial-intelligence company, founded in 2016 and headquartered in Mumbai, India, that builds regulator-cleared deep-learning software for medical imaging. Its products read chest X-rays (qXR), head and chest CT (qER, qCT), and musculoskeletal X-rays (qMSK) to detect, quantify and triage findings such as tuberculosis, lung nodules, intracranial hemorrhage, midline shift, cranial fracture, pneumothorax and pleural effusion, typically in under a minute. The company exposes these models to partners through the Qure Platform API, a token-authenticated DICOM ingest and results-retrieval REST interface documented at docs.qure.ai, alongside an on-premises Gateway deployment and the Qure.ai clinical app. Qure.ai holds multiple US FDA 510(k) clearances and EU MDR/MDD CE certifications and reports deployment across more than 85 countries.

Qure.ai publishes 3 APIs on the APIs.io network: Fetch Results API, Initiate Computation API, and Upload DICOMs API. Tagged areas include Artificial Intelligence, Healthcare, Medical Imaging, Radiology, and Machine-Learning.

Qure.ai’s developer surface includes documentation, API reference, getting-started guide, support, engineering blog, signup flow, changelog, and 25 more developer resources.

🌐 Visit website 📡 Source on GitHub

49.3/100 developing ▬ flat Agent 27/100 agent aware saas Full breakdown ↓
scored 2026-09-01 · rubric v0.17.2

4 APIs

Artificial Intelligence Healthcare Medical Imaging Radiology Machine-Learning DICOM Diagnostics Clinical Decision Support Health Technology Company

What this lets a business do 1

Business capabilities this provider's published APIs can perform, derived from its own contracts. Browse all capabilities →

Diagnostic Services Management

BC-2860

Upload DICOMs

POST /studies

Kin Score

Kin Score How this is scored →
scored 2026-09-01 · rubric v0.17.2

Composite quality — 49.3/100 · developing

Contract Quality 10.3 / 21

Developer Ergonomics 10.0 / 17

Access Clarity 7.2 / 17

Operational Transparency 2.0 / 11

Contract Governance 1.9 / 10

Discoverability 6.9 / 9

Regulatory Posture 7.1 / 15

Agent readiness — 27/100 · agent aware

Machine-Readable Contract 18 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

MCP Server 0 / 12

Machine-Readable Auth 10 / 10

Idempotency 0 / 9

Stable Error Semantics 8 / 8

Request/Response Examples 7 / 7

Rate-Limit Signaling 7 / 7

Typed Event Surface 0 / 6

Agent Skills 5 / 5

Well-Known Catalog 0 / 4

Consent & Bot Identity 0 / 3

A2A Agent Card 0 / 8

Dry-Run / Simulate Mode 0 / 4

Delegated User Identity 0 / 6

Protected Resource Metadata 0 / 5

Registration Without a Human 0 / 6

Agentic Commerce Surface 0 / 5

Regulatory Posture applies to this provider. Its tags matched the Health regime, so Regulatory Posture carries 15 points of the composite. If this regime is wrong for your business, say so on your provider repo — the applicability map is public and we will correct it.

The six quality facets above are damped to 85 points between them, because the conditional facet above carries the other 15. That is why each facet's contribution is shown against a damped maximum: raising a quality facet moves the composite by 85% of its nominal weight, not 100%. The full arithmetic is at apis.io/rating/.

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/qure.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 →

APIs 3

Individual APIs this provider publishes, each with its own machine-readable definition.

Rate Limits 1

Documented rate limits and quota policies.

Get Started 3

Portal, sign-up, and the first successful call

GettingStarted

GettingStarted

DeveloperPortal

DeveloperPortal

SignUp

SignUp

Documentation 2

Reference material describing how the API behaves

Documentation

Documentation

APIReference

APIReference

Agent Surfaces 4

MCP servers, agent skills, and machine-readable catalogs

LLMsTxt

LLMsTxt

MCPServerCandidate

MCPServerCandidate

AgentSkill

AgentSkill

WellKnownProbe

WellKnownProbe

Design & Contract 5

Pagination, idempotency, versioning, errors, and events

Lifecycle

Conventions

Conformance

ErrorCatalog

DataModel

Build 2

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

GitHubOrganization

Packages

Packages

Access & Security 3

Authentication, authorization, and security posture

Compliance

Compliance

Authentication

Authentication

DomainSecurity

DomainSecurity

Operate 5

Status, limits, changes, and where to get help

Support

StatusPage

ChangeLog

ChangeLog

RateLimits

Commercial 3

Pricing, plans, and the legal terms of use

TermsOfService

TermsOfService

PrivacyPolicy

PrivacyPolicy

Plans

Plans

Company 2

The organization behind the API

Website

Website

Blog

Blog

Other 3

Properties that don't map to a standard resource type

CapabilityMap

CapabilityMap

Overlay

Overlay

Overlay

Overlay

Source (apis.yml)

aid: qure.ai
name: Qure.ai
description: Qure.ai is a healthcare artificial-intelligence company, founded in 2016 and headquartered in Mumbai, India,
  that builds regulator-cleared deep-learning software for medical imaging. Its products read chest X-rays (qXR), head and
  chest CT (qER, qCT), and musculoskeletal X-rays (qMSK) to detect, quantify and triage findings such as tuberculosis, lung
  nodules, intracranial hemorrhage, midline shift, cranial fracture, pneumothorax and pleural effusion, typically in under
  a minute. The company exposes these models to partners through the Qure Platform API, a token-authenticated DICOM ingest
  and results-retrieval REST interface documented at docs.qure.ai, alongside an on-premises Gateway deployment and the Qure.ai
  clinical app. Qure.ai holds multiple US FDA 510(k) clearances and EU MDR/MDD CE certifications and reports deployment across
  more than 85 countries.
url: https://raw.githubusercontent.com/api-evangelist/qure.ai/refs/heads/main/apis.yml
x-type: company
x-source: harvest:secondary-market
x-tier: profiled
x-tier-reason: enrichment-pipeline
deliveryModel:
  model: saas
  open_source: false
  commercial: true
  callable_host: false
  label: Hosted service · you call their endpoint
  confidence: medium
  source:
  - openapi
  - pricing
  generated: '2026-08-28'
  method: derived
specificationVersion: '0.20'
created: '2026-08-26'
modified: '2026-08-26'
tags:
- Artificial Intelligence
- Healthcare
- Medical Imaging
- Radiology
- Machine-Learning
- DICOM
- Diagnostics
- Clinical Decision Support
- Health Technology
- Company
tags_raw:
- Artificial Intelligence
- Healthcare
- Medical Imaging
- Radiology
- Machine Learning
- DICOM
- Diagnostics
- Clinical Decision Support
- Health Technology
- Company
apis:
- aid: qure.ai:qure.ai-fetch-results-api
  name: Qure.ai Fetch Results API
  description: The Fetch Results API from Qure.ai — 3 operation(s) for fetch results.
  humanURL: https://docs.qure.ai/readme/api-reference
  baseURL: BASE_URL
  tags:
  - Fetch Results
  properties:
  - type: OpenAPI
    url: openapi/qure.ai-fetch-results-api-openapi.yml
  - type: Documentation
    url: https://docs.qure.ai/
  - type: APIReference
    url: https://docs.qure.ai/readme/api-reference
  - type: GettingStarted
    url: https://docs.qure.ai/readme/get-started
  - type: ErrorCatalog
    url: errors/qure.ai-problem-types.yml
  - type: DataModel
    url: data-model/qure.ai-data-model.yml
  - type: MCPServerCandidate
    url: mcp/qure.ai-mcp.yml
- aid: qure.ai:qure.ai-initiate-computation-api
  name: Qure.ai Initiate Computation API
  description: The Initiate Computation API from Qure.ai — 1 operation(s) for initiate computation.
  humanURL: https://docs.qure.ai/readme/api-reference
  baseURL: BASE_URL
  tags:
  - Initiate Computation
  properties:
  - type: OpenAPI
    url: openapi/qure.ai-initiate-computation-api-openapi.yml
  - type: Documentation
    url: https://docs.qure.ai/
  - type: APIReference
    url: https://docs.qure.ai/readme/api-reference
  - type: GettingStarted
    url: https://docs.qure.ai/readme/get-started
  - type: ErrorCatalog
    url: errors/qure.ai-problem-types.yml
  - type: DataModel
    url: data-model/qure.ai-data-model.yml
  - type: MCPServerCandidate
    url: mcp/qure.ai-mcp.yml
- aid: qure.ai:qure.ai-upload-dicoms-api
  name: Qure.ai Upload DICOMs API
  description: The Upload DICOMs API from Qure.ai — 1 operation(s) for upload dicoms.
  humanURL: https://docs.qure.ai/readme/api-reference
  baseURL: BASE_URL
  tags:
  - Upload DICOMs
  properties:
  - type: OpenAPI
    url: openapi/qure.ai-upload-dicoms-api-openapi.yml
  - type: Documentation
    url: https://docs.qure.ai/
  - type: APIReference
    url: https://docs.qure.ai/readme/api-reference
  - type: GettingStarted
    url: https://docs.qure.ai/readme/get-started
  - type: ErrorCatalog
    url: errors/qure.ai-problem-types.yml
  - type: DataModel
    url: data-model/qure.ai-data-model.yml
  - type: MCPServerCandidate
    url: mcp/qure.ai-mcp.yml
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: CapabilityMap
  url: capabilities/qure.ai-capability-edges.yml
  name: Qure.ai Business Capability Map
- type: Overlay
  url: overlays/qure.ai-platform-api-xray-v2-er-overlay.yaml
- type: Overlay
  url: overlays/qure.ai-platform-api-xray-ct-overlay.yaml
- type: Website
  url: https://www.qure.ai/
- type: Documentation
  url: https://docs.qure.ai/
- type: APIReference
  url: https://docs.qure.ai/readme/api-reference
- type: GettingStarted
  url: https://docs.qure.ai/readme/get-started
- type: DeveloperPortal
  url: https://documentation.qure.ai/
- type: Support
  url: https://www.qure.ai/contact-us
- type: Blog
  url: https://www.qure.ai/blog
- type: GitHubOrganization
  url: https://github.com/qureai
- type: SignUp
  url: https://app.qure.ai
- type: TermsOfService
  url: https://www.qure.ai/legal
- type: PrivacyPolicy
  url: https://www.qure.ai/privacy-policy
- type: Compliance
  url: https://www.qure.ai/regulatory-and-privacy
- type: StatusPage
  url: https://status.qure.ai/
- type: ChangeLog
  url: https://documentation.qure.ai/release-notes
- type: ChangeLog
  url: changelog/qure.ai-changelog.yml
- type: Lifecycle
  url: lifecycle/qure.ai-lifecycle.yml
- type: Authentication
  url: authentication/qure.ai-authentication.yml
- type: Conventions
  url: conventions/qure.ai-conventions.yml
- type: Conformance
  url: conformance/qure.ai-conformance.yml
- type: ErrorCatalog
  url: errors/qure.ai-problem-types.yml
- type: DataModel
  url: data-model/qure.ai-data-model.yml
- type: DomainSecurity
  url: security/qure.ai-domain-security.yml
- type: Packages
  url: packages/qure.ai-packages.yml
- type: Plans
  url: plans/qure.ai-plans-pricing.yml
- type: RateLimits
  url: rate-limits/qure.ai-rate-limits.yml
- type: LLMsTxt
  url: llms/qure.ai-llms.txt
- type: MCPServerCandidate
  url: mcp/qure.ai-mcp.yml
- type: AgentSkill
  url: skills/_index.yml
- type: WellKnownProbe
  url: well-known/qure.ai-well-known.yml
image: https://www.qure.ai/favicon.ico
x-secondary-market-listing: https://www.hiive.com/securities/qure.ai-stock
x-pointer-policy: 'Pointers deliberately WITHHELD, each because the underlying thing is genuinely absent: SDKs (no first-party
  client library on any registry — see packages/); Idempotency (no idempotency key documented or in either spec — see conventions/);
  Deprecation (an operation is labelled DEPRECATED in prose but no policy and no sunset date are published — see lifecycle/);
  Security (no security.txt, disclosure page or bug-bounty program found); TrustCenter (no trust.qure.ai and no trust portal);
  WellKnown / SecurityTxt (every /.well-known/ path 404s; status.qure.ai answers 200 to all of them including a control path
  and is a SPA catch-all); AgentCard (probed on every host, no hit — nothing written, per pipeline rule); Sandbox (test and
  pre-production environments exist but all credentials are issued by support@qure.ai; no self-serve console); AsyncAPI /
  Webhooks (no event, streaming or callback surface — the API is submit-then-poll); MCPServer (the mcp/ artifact is a DERIVED
  CANDIDATE with deployment.mode: none — Qure.ai ships no MCP server, so the pointer is typed MCPServerCandidate to keep it
  out of the scored MCP checks); CLI, Components, Postman, Roadmap, Vocabulary, DeclineCodes, Protobuf, WSDL, GraphQL (none
  published).'
x-enrichment:
  date: '2026-08-26'
  status: enriched
  artifacts_added: 24
  pass: local-v1

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Qure.ai

What this lets a business do 1

Kin Score

APIs 3

Qure.ai Fetch Results API

Qure.ai Initiate Computation API

Qure.ai Upload DICOMs API

Pricing Plans 1

Qure.Ai Plans Pricing