Unitlab AI

Unitlab AI is an enterprise multimodal data annotation platform for AI teams, providing a unified workspace to label images, video, audio, text, documents, and medical (DICOM/NIfTI) data with AI-assisted auto-labeling (including Segment Anything), human review workflows, dataset versioning and releases, and bring-your-own-model integration. Programmatic access comes through the Unitlab SDK API at api.unitlab.ai, consumed by the official `unitlab` Python SDK and CLI on PyPI, authenticated with API keys. Backed by 500 Global.

Unitlab AI publishes 2 APIs on the APIs.io network: Datasets API and Projects API. Tagged areas include Company, Data Annotation, Machine-Learning, Computer-Vision, and Datasets.

Unitlab AI’s developer surface includes documentation, API reference, getting-started guide, engineering blog, pricing, signup flow, authentication, and 18 more developer resources.

🌐 Visit website 📡 Source on GitHub

30.7/100 thin ▬ flat Agent 19/100 agent aware saas Full breakdown ↓
scored 2026-09-08 · rubric v0.20.0

1 APIs

Company Data Annotation Machine-Learning Computer-Vision Datasets Artificial Intelligence Labeling

Kin Score

Kin Score How this is scored →
scored 2026-09-08 · rubric v0.20.0

Composite quality — 30.7/100 · thin

Contract Quality 3.1 / 23

Developer Ergonomics 10.6 / 18

Access Clarity 6.9 / 18

Operational Transparency 0.3 / 12

Contract Governance 0.5 / 11

Discoverability 6.8 / 9

Create-or-Update Ergonomics 0.0 / 10

Agent readiness — 19/100 · 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 0 / 7

Rate-Limit Signaling 0 / 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 Well-Known Document 0 / 5

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.

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 github.com/api-evangelist/unitlab-ai: open an issue to ask a question, or submit a pull request to add artifacts. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

APIs 2

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

Unitlab AI Datasets API

Dataset releases

Unitlab AI Projects API

Annotation projects

Open Collections 3

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

API Collection

OPEN COLLECTION

Unitlab SDK Datasets API

OPEN COLLECTION

Unitlab SDK Datasets Projects API

OPEN COLLECTION

Security Posture 2

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

Unitlab Ai Authentication

apiKey · 1 scheme

SECURITY

Unitlab Ai Domain Security

TLSv1.3 · HSTS · DNSSEC · DMARC

SECURITY

Resources

Get Started 3

Portal, sign-up, and the first successful call

GettingStarted

GettingStarted

SignUp

SignUp

Login

Documentation 2

Reference material describing how the API behaves

Documentation

Documentation

APIReference

APIReference

Agent Surfaces 3

MCP servers, agent skills, and machine-readable catalogs

LLMsTxt

LLMsTxt

X-MCPServerCandidate

X-MCPServerCandidate

AgentSkill

AgentSkill

Design & Contract 5

Pagination, idempotency, versioning, errors, and events

Conformance

ErrorCatalog

Lifecycle

Conventions

DataModel

Build 4

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

Packages

SDKs

CLI

Access & Security 2

Authentication, authorization, and security posture

Authentication

Authentication

DomainSecurity

DomainSecurity

Commercial 3

Pricing, plans, and the legal terms of use

Pricing

Pricing

TermsOfService

TermsOfService

PrivacyPolicy

PrivacyPolicy

Company 2

The organization behind the API

Website

Website

Blog

Blog

Other 1

Properties that don't map to a standard resource type

Overlay

Overlay

Source (apis.yml)

aid: unitlab-ai
name: Unitlab AI
description: Unitlab AI is an enterprise multimodal data annotation platform for AI teams, providing a unified workspace to
  label images, video, audio, text, documents, and medical (DICOM/NIfTI) data with AI-assisted auto-labeling (including Segment
  Anything), human review workflows, dataset versioning and releases, and bring-your-own-model integration. Programmatic access
  comes through the Unitlab SDK API at api.unitlab.ai, consumed by the official `unitlab` Python SDK and CLI on PyPI, authenticated
  with API keys. Backed by 500 Global.
url: https://raw.githubusercontent.com/api-evangelist/unitlab-ai/refs/heads/main/apis.yml
deliveryModel:
  model: saas
  open_source: false
  commercial: true
  callable_host: true
  label: Hosted service · you call their endpoint
  confidence: high
  source:
  - openapi
  - pricing
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source:
  - authentication
  - security
  generated: '2026-09-03'
  method: derived
image: https://unitlab-storage.s3.us-east-2.amazonaws.com/Logo.png
x-type: company
x-source: vc-portfolio
x-backed-by:
- 500-global
x-tier: enriched
x-tier-reason: portfolio-lead
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-21'
tags:
- Company
- Data Annotation
- Machine-Learning
- Computer-Vision
- Datasets
- Artificial Intelligence
- Labeling
tags_raw:
- Company
- Data Annotation
- Machine Learning
- Computer Vision
- Datasets
- Artificial Intelligence
- Labeling
apis:
- aid: unitlab-ai:unitlab-ai-datasets-api
  name: Unitlab AI Datasets API
  description: Dataset releases
  humanURL: https://docs.unitlab.ai/cli-python-sdk/get-started
  baseURL: https://api.unitlab.ai
  tags:
  - Datasets
  properties:
  - type: OpenAPI
    url: openapi/unitlab-ai-datasets-api-openapi.yml
  - type: Documentation
    url: https://docs.unitlab.ai/cli-python-sdk/get-started
- aid: unitlab-ai:unitlab-ai-projects-api
  name: Unitlab AI Projects API
  description: Annotation projects
  humanURL: https://docs.unitlab.ai/cli-python-sdk/get-started
  baseURL: https://api.unitlab.ai
  tags:
  - Project
  tags_raw:
  - Projects
  properties:
  - type: OpenAPI
    url: openapi/unitlab-ai-projects-api-openapi.yml
  - type: Documentation
    url: https://docs.unitlab.ai/cli-python-sdk/get-started
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Overlay
  url: overlays/unitlab-ai-sdk-overlay.yaml
- type: Website
  url: https://unitlab.ai
- type: Documentation
  url: https://docs.unitlab.ai/
- type: APIReference
  url: https://docs.unitlab.ai/cli-python-sdk/unitlab-python-sdk
- type: GettingStarted
  url: https://docs.unitlab.ai/cli-python-sdk/get-started
- type: Blog
  url: https://blog.unitlab.ai/
- type: Pricing
  url: https://unitlab.ai/en/pricing
- type: SignUp
  url: https://app.unitlab.ai/register
- type: Login
  url: https://app.unitlab.ai/
- type: TermsOfService
  url: https://unitlab.ai/en/term-of-use
- type: PrivacyPolicy
  url: https://unitlab.ai/en/privacy-policy
- type: GitHubOrganization
  url: https://github.com/teamunitlab
- type: Authentication
  url: authentication/unitlab-ai-authentication.yml
- type: DomainSecurity
  url: security/unitlab-ai-domain-security.yml
- type: Packages
  url: packages/unitlab-ai-packages.yml
- type: SDKs
  url: packages/unitlab-ai-packages.yml
- type: CLI
  url: cli/unitlab-ai-cli.yml
- type: LLMsTxt
  url: llms/unitlab-ai-llms.txt
- type: X-MCPServerCandidate
  url: mcp/unitlab-ai-mcp.yml
  note: 'Renamed from MCPServer 2026-09-03 (roadmap#247): the manifest self-describes as status: candidate — a tool list derived
    from the published API contracts, not an existing server. The scorer already read the manifest and reported mcp_server
    correctly; the MCPServer type was crediting the artifact-type surfaces with a server that does not exist.'
- type: Conformance
  url: conformance/unitlab-ai-conformance.yml
- type: ErrorCatalog
  url: errors/unitlab-ai-problem-types.yml
- type: Lifecycle
  url: lifecycle/unitlab-ai-lifecycle.yml
- type: Conventions
  url: conventions/unitlab-ai-conventions.yml
- type: DataModel
  url: data-model/unitlab-ai-data-model.yml
- type: AgentSkill
  url: skills/_index.yml
x-enrichment:
  date: '2026-07-21'
  status: enriched
  artifacts_added: 17
  pass: local-v1

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