Segments.ai

Segments.ai is a data-labeling platform for computer vision, supporting 2D image segmentation and vectors as well as 3D point cloud and multi-sensor fusion annotation. Its REST API and Python SDK let teams manage datasets, samples, labels, labelsets, and versioned releases programmatically for building training data pipelines.

Segments.ai publishes 5 API contracts indexed on the APIs.io network, including Datasets API, Labels API, Releases API, and 2 more. Tagged areas include Data Labeling, Computer Vision, Point Cloud, Annotation, and Machine Learning.

The Segments.ai catalog on APIs.io includes 1 Spectral governance ruleset.

Segments.ai’s developer surface includes pricing, authentication, documentation, engineering blog, and 8 more developer resources.

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34.1/100 thin ▬ flat Agent 19/100 agent aware Heartbeat 75/100 alive open core · MIT Full breakdown ↓
scored 2026-11-13 · rubric v0.28.0 · Show this score on your site →

AccessEnterprise

1 published contract

Data Labeling Computer Vision Point Cloud Annotation Machine Learning

Kin Score

Kin Score How this is scored →
scored 2026-11-13 · rubric v0.28.0

Composite quality — 34.1/100 · thin

Contract Quality 8.3 / 19

Developer Ergonomics 4.8 / 15

Access Clarity 5.1 / 15

Operational Transparency 1.2 / 10

Contract Governance 1.2 / 9

Discoverability 5.0 / 8

Regulatory Posture 0.8 / 15

Create-or-Update Ergonomics 2.2 / 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 Ask about this →
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) Ask about this →
Stable Error Semantics +8 pts — OpenAPI $refs a shared error schema across 4xx/5xx responses (verified), else common[].type includes ErrorCatalog / ErrorCodes / DeclineCodes Ask about this →
A2A Agent Card +8 pts — a2a/-a2a.yml manifest, graded on conformance.grade against A2A 1.0.0 Ask about this →
Request/Response Examples +7 pts — share of operations carrying request/response examples; else an Examples / Code Samples link Ask about this →
Registration Without a Human +6 pts — a `registration_endpoint` in the served RFC 8414 / OIDC discovery document Ask about this →

10 more unmet checks in the Agent Readiness table above.

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

Contract Quality scores 44.1 — up to +14.0 composite points Ask about this →
Developer Ergonomics scores 32.1 — up to +13.6 composite points Ask about this →
Access Clarity scores 34.0 — up to +13.2 composite points Ask about this →

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.

Not sure how this applies to your stack? Ask about any one item. Kin Lane reads every question, looks at your profile and your situation, and replies with what a fix would take — scoped to that one area, priced up front, yours whether you ship it or not. Ask a question →

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/segments-ai/apis.yml: open an issue on github.com/api-evangelist/segments-ai 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 →

Markets this provider is in provisional

The Kin Score Market layer reads a provider inside its market: its position, and how deep its integrations go. Depth is only comparable within a position. Provisional and unweighted: not part of the Kin Score or agent readiness.

Market	Position	Depth	Registered MCP server	Declares compatibility
ONVIF Video Analytics (video surveillance, edge cameras, computer vision)	builds-on	17.2 (thin)	-	-
Hugging Face Hub Organisations	builds-on	17.2 (thin)	-	-

Registered MCP server and declares compatibility are report only — not weighted. Undeclared means we found nothing we can read, so there is no number: we never infer integrations.

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 5

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

Segments.ai Datasets API

The Datasets API from Segments.ai — 4 operation(s) for datasets.

Segments.ai Labels API

The Labels API from Segments.ai — 1 operation(s) for labels.

Segments.ai Releases API

The Releases API from Segments.ai — 2 operation(s) for releases.

Segments.ai Samples API

The Samples API from Segments.ai — 2 operation(s) for samples.

Segments.ai Label Sets API

The Label Sets API from Segments.ai — 2 operation(s) for label sets.

Open Collections 6

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

Segments.ai Datasets API

OPEN COLLECTION

Segments.ai Datasets Labels API

OPEN COLLECTION

Segments.ai Datasets Labelsets API

OPEN COLLECTION

Segments.ai Datasets Releases API

OPEN COLLECTION

Segments.ai Datasets Samples API

OPEN COLLECTION

Segments.ai API

OPEN COLLECTION

Segments.ai API pricing

Prices published by Segments.ai, read 2026-10-07 from segments.ai/pricing/.

Plan	Price
Core	Starting at 3,600 hours/yr of labeling usage (equivalent to $2.67/hour) Includes: Unlimited seats, projects, images & point clouds, unlimited API & SDK access
Fusion	Custom quote Includes: Starting at 5,000 hours/yr of labeling usage
Enterprise	Custom quote Includes: Includes +150,000 hours/year of labeling usage

Plan details, limits and sources →

Rate limits

REST Requests: see provider documentation requests
Sample / Release Pagination: paginated results
Asset Upload: see provider documentation uploads

Compiled by API Evangelist, not yet checked against Segments.ai's documentation. Rate-limit details →

Pricing Plans 1

Published pricing tiers and plan structures.

Segments.ai Plans Pricing

3 plans

PLANS

Rate Limits 1

Documented rate limits and quota policies.

Segments.ai Rate Limits

3 limits

RATE LIMITS

FinOps 1

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

Segments.ai Finops

FINOPS

Spectral Rules 1

Spectral governance rulesets for linting and validating these APIs. Counts are the severity each rule declares, not results of running them.

Segments.ai API Rules

58 rules · 55 error-severity 2 warn-severity 1 info-severity

SPECTRAL

Security Posture 2

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

Segments.ai Authentication

apiKey · 1 scheme

SECURITY

Segments.ai Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Agentic Access (API Evangelist recommendations) 1

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

Segments.ai Agentic Access

23 operations · 13 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 3

Pricing, plans, and the legal terms of use

Pricing

Pricing

Plans

Plans

FinOps

FinOps

Company 3

The organization behind the API

LinkedIn

Website

Website

Blog

Blog

Source (apis.yml)

aid: segments-ai
url: https://raw.githubusercontent.com/api-evangelist/segments-ai/refs/heads/main/apis.yml
name: Segments.ai
kind: company
description: Segments.ai is a data-labeling platform for computer vision, supporting 2D image segmentation and vectors as
  well as 3D point cloud and multi-sensor fusion annotation. Its REST API and Python SDK let teams manage datasets, samples,
  labels, labelsets, and versioned releases programmatically for building training data pipelines.
deliveryModel:
  model: open-core
  license: MIT
  license_evidence:
    repo: segments-ai/segments-ai
    spdx: MIT
    stars: 28
  open_source: true
  commercial: true
  callable_host: true
  label: Open core · an OSS project plus a commercial hosted product
  confidence: medium
  source:
  - openapi
  - pricing
  - repository-license
  generated: '2026-09-25'
  method: derived
accessModel:
  pricing: enterprise
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Enterprise
  confidence: medium
  source:
  - plans
  - authentication
  - security
  generated: '2026-11-13'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/segments-ai.png
x-docs-platform: gitbook
x-docs-platform-confidence: high
x-docs-platform-checked: 2026-10-04
tags:
- Data Labeling
- Computer Vision
- Point Cloud
- Annotation
- Machine Learning
tags_raw:
- Data Labeling
- Computer Vision
- Point Cloud
- Annotation
- Machine Learning
- Computer-Vision
- Machine-Learning
created: '2026-06-21'
modified: '2026-06-21'
specificationVersion: '0.23'
apis:
- aid: segments-ai:segments-ai-datasets-api
  name: Segments.ai Datasets API
  description: The Datasets API from Segments.ai — 4 operation(s) for datasets.
  humanURL: https://docs.segments.ai/reference/api
  baseURL: https://api.segments.ai
  tags:
  - Datasets
  properties:
  - type: OpenAPI
    url: openapi/segments-ai-datasets-api-openapi.yml
  - type: Documentation
    url: https://docs.segments.ai/background/main-concepts
  - type: APIReference
    url: https://docs.segments.ai/reference/api
  - type: PostmanCollection
    url: collections/segments-ai.postman_collection.json
  - type: OpenCollection
    url: collections/segments-ai.opencollection.json
  - type: GitHub
    url: https://github.com/segments-ai/segments-ai
- aid: segments-ai:segments-ai-labels-api
  name: Segments.ai Labels API
  description: The Labels API from Segments.ai — 1 operation(s) for labels.
  humanURL: https://docs.segments.ai/reference/api
  baseURL: https://api.segments.ai
  tags:
  - Labels
  properties:
  - type: OpenAPI
    url: openapi/segments-ai-labels-api-openapi.yml
  - type: Documentation
    url: https://docs.segments.ai/background/main-concepts
  - type: APIReference
    url: https://docs.segments.ai/reference/api
  - type: PostmanCollection
    url: collections/segments-ai.postman_collection.json
  - type: OpenCollection
    url: collections/segments-ai.opencollection.json
  - type: GitHub
    url: https://github.com/segments-ai/segments-ai
- aid: segments-ai:segments-ai-releases-api
  name: Segments.ai Releases API
  description: The Releases API from Segments.ai — 2 operation(s) for releases.
  humanURL: https://docs.segments.ai/reference/api
  baseURL: https://api.segments.ai
  tags:
  - Releases
  properties:
  - type: OpenAPI
    url: openapi/segments-ai-releases-api-openapi.yml
  - type: Documentation
    url: https://docs.segments.ai/background/main-concepts
  - type: APIReference
    url: https://docs.segments.ai/reference/api
  - type: PostmanCollection
    url: collections/segments-ai.postman_collection.json
  - type: OpenCollection
    url: collections/segments-ai.opencollection.json
  - type: GitHub
    url: https://github.com/segments-ai/segments-ai
- aid: segments-ai:segments-ai-samples-api
  name: Segments.ai Samples API
  description: The Samples API from Segments.ai — 2 operation(s) for samples.
  humanURL: https://docs.segments.ai/reference/api
  baseURL: https://api.segments.ai
  tags:
  - Samples
  properties:
  - type: OpenAPI
    url: openapi/segments-ai-samples-api-openapi.yml
  - type: Documentation
    url: https://docs.segments.ai/background/main-concepts
  - type: APIReference
    url: https://docs.segments.ai/reference/api
  - type: PostmanCollection
    url: collections/segments-ai.postman_collection.json
  - type: OpenCollection
    url: collections/segments-ai.opencollection.json
  - type: GitHub
    url: https://github.com/segments-ai/segments-ai
- aid: segments-ai:segments-ai-label-sets-api
  name: Segments.ai Label Sets API
  description: The Label Sets API from Segments.ai — 2 operation(s) for label sets.
  humanURL: https://docs.segments.ai/reference/api
  baseURL: https://api.segments.ai
  tags:
  - Label Sets
  properties:
  - type: OpenAPI
    url: openapi/segments-ai-label-sets-api-openapi.yml
  - type: Documentation
    url: https://docs.segments.ai/background/main-concepts
  - type: APIReference
    url: https://docs.segments.ai/reference/api
  - type: PostmanCollection
    url: collections/segments-ai.postman_collection.json
  - type: OpenCollection
    url: collections/segments-ai.opencollection.json
  - type: GitHub
    url: https://github.com/segments-ai/segments-ai
common:
- type: Pricing
  url: https://segments.ai/pricing/
- type: AgenticAccess
  url: agentic-access/segments-ai-agentic-access.yml
- type: DomainSecurity
  url: security/segments-ai-domain-security.yml
- type: Authentication
  url: authentication/segments-ai-authentication.yml
- type: GitHubOrganization
  url: https://github.com/segments-ai
- type: LinkedIn
  url: https://www.linkedin.com/company/segments-ai
- type: Website
  url: https://segments.ai
- type: Documentation
  url: https://docs.segments.ai
- type: Plans
  url: plans/segments-ai-plans-pricing.yml
- type: RateLimits
  url: rate-limits/segments-ai-rate-limits.yml
- type: FinOps
  url: finops/segments-ai-finops.yml
- type: Blog
  url: https://segments.ai/blog/
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com

Segments.ai API — frequently asked questions

Does Segments.ai have an API?

Yes. APIs.io lists 5 APIs from Segments.ai, including Segments.ai Datasets API, Segments.ai Labels API and Segments.ai Releases API, and 2 more.

Is there an OpenAPI specification for the Segments.ai API?

Yes. APIs.io indexes 5 OpenAPI specifications for Segments.ai, each linked for download from this page.

How do I authenticate with the Segments.ai API?

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

How much does the Segments.ai API cost?

Segments.ai publishes its prices; its Core plan is Starting at 3,600 hours/yr of labeling usage (equivalent to $2.67/hour) as of 2026-10-07. APIs.io lists 3 pricing plans for Segments.ai, with each plan's price, limits and inclusions under Pricing on this page.

Is the Segments.ai API ready for AI agents?

Segments.ai has a Kin Score of 34.1 out of 100 (thin) and an Agent Readiness score of 19.0 (agent-aware), scored by API Evangelist on 2026-11-13.

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