Deepchecks

Deepchecks is an ML and LLM testing, evaluation, and monitoring platform. Its cloud LLM Evaluation product exposes a REST API for logging LLM interactions, managing applications and versions, retrieving annotations, and configuring evaluation properties, while its open-source Python packages provide continuous validation of tabular, computer-vision, and LLM data and models.

Deepchecks publishes 7 API contracts indexed on the APIs.io network, including Application Versions API, Applications API, Interactions API, and 4 more. Tagged areas include Artificial Intelligence, LLM, Evaluation, Testing, and Monitoring.

The Deepchecks catalog on APIs.io includes 1 Spectral governance ruleset.

Deepchecks’ developer surface includes authentication, documentation, and 9 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

24.5/100 emerging ▬ flat Agent 19/100 agent aware Heartbeat 29/100 slowing Full breakdown ↓
scored 2026-11-06 · rubric v0.27.0 · Show this score on your site →

AccessFreemiumSelf serveFree trial⚡ Free to try

1 published contract

Artificial Intelligence LLM Evaluation Testing Monitoring

What this lets a business do 1

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

Information & Data Management

BC-610

Application VersionsApplicationsInteractions

POST /api/v1/application-versions/{application_version_id}/interactions

Kin Score

Kin Score How this is scored →
scored 2026-11-06 · rubric v0.27.0

Composite quality — 24.5/100 · emerging

Contract Quality 8.0 / 19

Developer Ergonomics 3.0 / 15

Access Clarity 1.2 / 15

Operational Transparency 1.0 / 10

Contract Governance 1.2 / 9

Discoverability 5.0 / 8

Regulatory Posture 1.6 / 15

Create-or-Update Ergonomics 0.0 / 10

Agent readiness — 19/100 · agent aware

Machine-Readable Contract 18 / 18

Agentic Access Contract 10 / 10

Documented Reversibility 0 / 6

MCP Server 0 / 12

Machine-Readable Auth 10 / 10

Idempotency 0 / 9

Stable Error Semantics 0 / 8

Request/Response Examples 0 / 7

Rate-Limit Signaling 7 / 7

Typed Event Surface 0 / 6

Agent Skills 0 / 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 Well-Known Document 0 / 5

Pagination 0 / 5

Distinct Operations 3 / 3

MCP Tool Quality 6 / 6

Regulatory Posture applies to this provider. Its tags matched the Horizontal (data, software, accessibility, platform) 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.

Create-or-Update Ergonomics applies to this provider. This API accepts writes, so it carries 10 points of the composite. It is scored from the published contracts themselves: whether a caller can create-or-update in one call, whether the write accepts a key the caller already holds, and whether the response says which branch ran. Without that, every write needs a search-and-branch in front of it, and the first time that check is skipped a duplicate record is created. Scored against the observed mean rather than raw — a provider at the catalog average is unchanged by this facet, not penalised by it.

The six quality facets above are damped to 75 points between them, because the conditional facet above carries the other 25. That is why each facet's contribution is shown against a damped maximum: raising a quality facet moves the composite by 75% of its nominal weight, not 100%. The full arithmetic is at apis.io/rating/.

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Agent readiness — checks not met, largest first (exact, from this profile):

MCP Server +12 pts — deployment.mode + probe verdict on the mcp/ manifest, not the pointer; an unprobed slug falls back to authorship
Idempotency +9 pts — OpenAPI mutating operations declare an idempotency key — a header, a request-body property, or a named de-duplication token whose own description says so (verified); else common[].type matches /idempoten/i (documented)
Stable Error Semantics +8 pts — OpenAPI $refs a shared error schema across 4xx/5xx responses (verified), else common[].type includes ErrorCatalog / ErrorCodes / DeclineCodes
A2A Agent Card +8 pts — a2a/-a2a.yml manifest, graded on conformance.grade against A2A 1.0.0
Request/Response Examples +7 pts — share of operations carrying request/response examples; else an Examples / Code Samples link
Registration Without a Human +6 pts — a `registration_endpoint` in the served RFC 8414 / OIDC discovery document

10 more unmet checks in the Agent Readiness table above.

Kin Score — facets with the most composite points still available (weight × headroom):

Access Clarity scores 7.9 — up to +18.4 composite points
Developer Ergonomics scores 20.2 — up to +16.0 composite points
Contract Quality scores 42.6 — up to +14.4 composite points

Each check links to what satisfies it. Publish the artifact, or tell us where it already lives, and the score moves on the next scoring run.

Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. Every facet and dimension name above is a link: it opens that measurement's own page — what it means, the exact checks that feed it, how the whole catalog distributes on it, and the providers at the top of it. This rating is computed from the provider profile at artifacts.apis.io/deepchecks/apis.yml: open an issue on github.com/api-evangelist/deepchecks to ask a question or point us at an artifact you publish. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

Standards implemented 1

Standards this provider implements or carries. De facto ones are profiled and measured by the API Commons; formal ones come from the standards directory and are linked by the provider's own tags. The evidence column says how each claim was established — not that it was made.

OpenAPI

measured — observed by APIs.io (published)

APIs 7

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

Deepchecks Open-Source Testing

The AGPL-3.0 licensed open-source Python package for continuous validation of tabular, computer-vision, and LLM/NLP data and models. Distributed via PyPI (pip install deepchecks...

Deepchecks Application Versions API

Versions of an evaluation application.

Deepchecks Applications API

Evaluation applications.

Deepchecks Interactions API

LLM interaction logging and retrieval.

Deepchecks Properties API

LLM property definitions.

Deepchecks Spans API

Raw tracing spans.

Deepchecks System API

Backend metadata.

Scroll for all 7

Open Collections 7

Open, tool-agnostic API collections (OpenAPI-derived and Bruno).

Deepchecks LLM Evaluation Application Versions API

OPEN COLLECTION

Deepchecks LLM Evaluation Application Versions Applications API

OPEN COLLECTION

Deepchecks LLM Evaluation Application Versions Interactions API

OPEN COLLECTION

Deepchecks LLM Evaluation Application Versions Properties API

OPEN COLLECTION

Deepchecks LLM Evaluation Application Versions Spans API

OPEN COLLECTION

Deepchecks LLM Evaluation Application Versions System API

OPEN COLLECTION

Deepchecks LLM Evaluation API

OPEN COLLECTION

Scroll for all 7

Deepchecks API pricing

Not yet checked against Deepchecks's own pricing page. Compiled by API Evangelist on 2026-06-20 from www.deepchecks.com/pricing/; confirm before you rely on a figure. A free plan or tier is listed.

Plan	Price
Open Source free	—
Basic subscription	—
Scale subscription	—
Enterprise enterprise	—

Plan details, limits and sources →

Rate limits

DPUs Per Month: see plan (5K Basic / 20K Scale / custom Enterprise) dpus
AI Applications: see plan (1 Basic / 3 Scale / custom Enterprise) applications
Seats: see plan (3 Basic / 5 Scale / custom Enterprise) seats

Compiled by API Evangelist, not yet checked against Deepchecks's documentation. All 4 limits →

Pricing Plans 1

Published pricing tiers and plan structures.

Deepchecks Plans Pricing

4 plans

PLANS

Rate Limits 1

Documented rate limits and quota policies.

Deepchecks Rate Limits

4 limits

RATE LIMITS

Service Levels 1

Uptime the provider promises or reports, as SLA4OAI. Read from its own pages; APIs.io runs no monitors.

Deepchecks

SLA

FinOps 1

Cost, billing, and metering signals for API financial operations.

Deepchecks Finops

FINOPS

Spectral Rules 1

Spectral governance rulesets for linting and validating these APIs.

Deepchecks API Rules

62 rules · 59 errors 1 warnings 2 info

SPECTRAL

Security Posture 2

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

Deepchecks Authentication

http · 1 scheme

SECURITY

Deepchecks Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Agentic Access 1

Recommended x-agentic-access execution contracts for AI agents.

Deepchecks Agentic Access

12 operations · 5 acting

AGENTIC

Resources

Documentation 1

Reference material describing how the API behaves

Documentation

Documentation

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

AgenticAccess

AgenticAccess

Build 1

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

GitHubOrganization

Access & Security 2

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Authentication

Authentication

Operate 1

Status, limits, changes, and where to get help

RateLimits

RateLimits

Commercial 2

Pricing, plans, and the legal terms of use

Plans

Plans

FinOps

FinOps

Company 2

The organization behind the API

LinkedIn

Website

Website

Other 1

Properties that don't map to a standard resource type

CapabilityMap

CapabilityMap

Source (apis.yml)

aid: deepchecks
url: https://raw.githubusercontent.com/api-evangelist/deepchecks/refs/heads/main/apis.yml
name: Deepchecks
kind: company
description: Deepchecks is an ML and LLM testing, evaluation, and monitoring platform. Its cloud LLM Evaluation product exposes
  a REST API for logging LLM interactions, managing applications and versions, retrieving annotations, and configuring evaluation
  properties, while its open-source Python packages provide continuous validation of tabular, computer-vision, and LLM data
  and models.
deliveryModel:
  model: unknown
  license_evidence:
    repo: deepchecks/deepchecks
    spdx: NOASSERTION
    stars: 4056
  open_source: unknown
  commercial: true
  callable_host: false
  label: Delivery model not determined — needs a product licence on record
  confidence: low
  source:
  - openapi
  - pricing
  - repository-unlicensed
  generated: '2026-09-25'
  method: derived
accessModel:
  pricing: freemium
  onboarding: self-serve
  trial: true
  try_now: true
  public: false
  gated: none
  gated_source:
  - onboarding
  label: Freemium (free trial) · Self-serve signup
  confidence: medium
  source:
  - plans
  - authentication
  - security
  generated: '2026-11-06'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/deepchecks.png
x-docs-platform: readme
x-docs-platform-confidence: high
x-docs-platform-checked: 2026-09-25
tags:
- Artificial Intelligence
- LLM
- Evaluation
- Testing
- Monitoring
tags_raw:
- AI
- LLM
- Evaluation
- Testing
- Monitoring
created: '2026-06-20'
modified: '2026-06-20'
specificationVersion: '0.23'
apis:
- aid: deepchecks:open-source-testing
  name: Deepchecks Open-Source Testing
  tags:
  - Open Source
  - Testing
  - Validation
  - Python
  tags_raw:
  - Open Source
  - Testing
  - Validation
  - Python
  - Open-Source
  image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/apis-json-logo.jpg
  humanURL: https://github.com/deepchecks/deepchecks
  baseURL: https://github.com/deepchecks/deepchecks
  properties:
  - url: https://docs.deepchecks.com/stable/getting-started/welcome.html
    type: Documentation
  - url: https://github.com/deepchecks/deepchecks
    type: GitHub
  description: The AGPL-3.0 licensed open-source Python package for continuous validation of tabular, computer-vision, and
    LLM/NLP data and models. Distributed via PyPI (pip install deepchecks); a Python library rather than a hosted HTTP API.
- aid: deepchecks:deepchecks-application-versions-api
  name: Deepchecks Application Versions API
  description: Versions of an evaluation application.
  humanURL: https://llmdocs.deepchecks.com/reference
  baseURL: https://app.llm.deepchecks.com/api/v1
  tags:
  - Application Versions
  properties:
  - type: OpenAPI
    url: openapi/deepchecks-application-versions-api-openapi.yml
  - type: Documentation
    url: https://llmdocs.deepchecks.com/docs/deepchecks-sdk
  - type: APIReference
    url: https://llmdocs.deepchecks.com/reference
  - type: PostmanCollection
    url: collections/deepchecks.postman_collection.json
  - type: OpenCollection
    url: collections/deepchecks.opencollection.json
  - type: GitHub
    url: https://github.com/deepchecks
- aid: deepchecks:deepchecks-applications-api
  name: Deepchecks Applications API
  description: Evaluation applications.
  humanURL: https://llmdocs.deepchecks.com/reference
  baseURL: https://app.llm.deepchecks.com/api/v1
  tags:
  - Application
  tags_raw:
  - Applications
  properties:
  - type: OpenAPI
    url: openapi/deepchecks-applications-api-openapi.yml
  - type: Documentation
    url: https://llmdocs.deepchecks.com/docs/deepchecks-sdk
  - type: APIReference
    url: https://llmdocs.deepchecks.com/reference
  - type: PostmanCollection
    url: collections/deepchecks.postman_collection.json
  - type: OpenCollection
    url: collections/deepchecks.opencollection.json
  - type: GitHub
    url: https://github.com/deepchecks
- aid: deepchecks:deepchecks-interactions-api
  name: Deepchecks Interactions API
  description: LLM interaction logging and retrieval.
  humanURL: https://llmdocs.deepchecks.com/reference
  baseURL: https://app.llm.deepchecks.com/api/v1
  tags:
  - Interactions
  properties:
  - type: OpenAPI
    url: openapi/deepchecks-interactions-api-openapi.yml
  - type: Documentation
    url: https://llmdocs.deepchecks.com/docs/deepchecks-sdk
  - type: APIReference
    url: https://llmdocs.deepchecks.com/reference
  - type: PostmanCollection
    url: collections/deepchecks.postman_collection.json
  - type: OpenCollection
    url: collections/deepchecks.opencollection.json
  - type: GitHub
    url: https://github.com/deepchecks
- aid: deepchecks:deepchecks-properties-api
  name: Deepchecks Properties API
  description: LLM property definitions.
  humanURL: https://llmdocs.deepchecks.com/reference
  baseURL: https://app.llm.deepchecks.com/api/v1
  tags:
  - Properties
  properties:
  - type: OpenAPI
    url: openapi/deepchecks-properties-api-openapi.yml
  - type: Documentation
    url: https://llmdocs.deepchecks.com/docs/deepchecks-sdk
  - type: APIReference
    url: https://llmdocs.deepchecks.com/reference
  - type: PostmanCollection
    url: collections/deepchecks.postman_collection.json
  - type: OpenCollection
    url: collections/deepchecks.opencollection.json
  - type: GitHub
    url: https://github.com/deepchecks
- aid: deepchecks:deepchecks-spans-api
  name: Deepchecks Spans API
  description: Raw tracing spans.
  humanURL: https://llmdocs.deepchecks.com/reference
  baseURL: https://app.llm.deepchecks.com/api/v1
  tags:
  - Spans
  properties:
  - type: OpenAPI
    url: openapi/deepchecks-spans-api-openapi.yml
  - type: Documentation
    url: https://llmdocs.deepchecks.com/docs/deepchecks-sdk
  - type: APIReference
    url: https://llmdocs.deepchecks.com/reference
  - type: PostmanCollection
    url: collections/deepchecks.postman_collection.json
  - type: OpenCollection
    url: collections/deepchecks.opencollection.json
  - type: GitHub
    url: https://github.com/deepchecks
- aid: deepchecks:deepchecks-system-api
  name: Deepchecks System API
  description: Backend metadata.
  humanURL: https://llmdocs.deepchecks.com/reference
  baseURL: https://app.llm.deepchecks.com/api/v1
  tags:
  - System
  properties:
  - type: OpenAPI
    url: openapi/deepchecks-system-api-openapi.yml
  - type: Documentation
    url: https://llmdocs.deepchecks.com/docs/deepchecks-sdk
  - type: APIReference
    url: https://llmdocs.deepchecks.com/reference
  - type: PostmanCollection
    url: collections/deepchecks.postman_collection.json
  - type: OpenCollection
    url: collections/deepchecks.opencollection.json
  - type: GitHub
    url: https://github.com/deepchecks
common:
- type: CapabilityMap
  url: capabilities/deepchecks-capability-edges.yml
  name: Deepchecks Business Capability Map
- type: AgenticAccess
  url: agentic-access/deepchecks-agentic-access.yml
- type: DomainSecurity
  url: security/deepchecks-domain-security.yml
- type: Authentication
  url: authentication/deepchecks-authentication.yml
- type: GitHubOrganization
  url: https://github.com/deepchecks
- type: LinkedIn
  url: https://www.linkedin.com/company/deepchecks
- type: Website
  url: https://www.deepchecks.com
- type: Documentation
  url: https://llmdocs.deepchecks.com
- type: Plans
  url: plans/deepchecks-plans-pricing.yml
- type: RateLimits
  url: rate-limits/deepchecks-rate-limits.yml
- type: FinOps
  url: finops/deepchecks-finops.yml
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com

Deepchecks API — frequently asked questions

Does Deepchecks have an API?

Yes. APIs.io lists 7 APIs from Deepchecks, including Deepchecks Open-Source Testing, Deepchecks Application Versions API and Deepchecks Applications API, and 4 more.

Is there an OpenAPI specification for the Deepchecks API?

Yes. APIs.io indexes 6 OpenAPI specifications for Deepchecks, each linked for download from this page.

How do I authenticate with the Deepchecks API?

Deepchecks uses bearer-token authentication (http · 1 scheme). The details are profiled on APIs.io as Deepchecks Authentication.

How much does the Deepchecks API cost?

APIs.io lists 4 pricing plans for Deepchecks, with each plan's price, limits and inclusions under Pricing on this page.

Is the Deepchecks API ready for AI agents?

Deepchecks has a Kin Score of 24.5 out of 100 (emerging) and an Agent Readiness score of 19.0 (agent-aware), scored by API Evangelist on 2026-11-06.

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