Adaption website screenshot

Adaption

Adaption (Adaption Labs) is a San Francisco AI research company building adaptive, continuously-learning AI systems rather than relying on ever-larger static models. Founded in 2026 by former Cohere leaders Sara Hooker and Sudip Roy, it exited stealth with a $50M seed round led by Emergence Capital. Its first product, Adaptive Data, exposes a REST API and official Python SDK to ingest, adapt, evaluate, and export model-ready training datasets — folding data-optimization techniques usually reserved for frontier labs into a self-serve workflow for everyday teams.

Adaption publishes 2 APIs on the APIs.io network: Datasets API and Upload API. Tagged areas include Company, Ai, Artificial Intelligence, Machine Learning, and Training Data.

Adaption’s developer surface includes documentation, API reference, getting-started guide, engineering blog, signup flow, support, authentication, and 17 more developer resources.

🌐 Visit website 📡 Source on GitHub
44.6/100 thin ▬ flat Agent 64/100 agent native Full breakdown ↓
scored 2026-07-27 · rubric v0.5
2 APIs 1 MCP Servers
CompanyAiArtificial IntelligenceMachine LearningTraining DataDatasetsData AugmentationLLMModel TrainingDeveloper Tools

Kin Score

Kin Score Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5
Composite quality — 44.6/100 · thin
Contract Quality 13.7 / 25
Developer Ergonomics 14.8 / 20
Commercial Clarity 6.8 / 20
Operational Transparency 0.0 / 13
Governance 0.0 / 12
Discoverability 9.3 / 10
Agent readiness — 64/100 · agent native
Machine-Readable Contract 18 / 18
Agentic Access Contract 0 / 15
MCP Server 12 / 12
Machine-Readable Auth 10 / 10
Idempotency 9 / 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 4 / 4
Consent & Bot Identity 0 / 3
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/adaption: 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 2

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

Adaption Datasets API

Create, list, run, evaluate, download, and publish adaptive datasets.

Adaption Upload API

Pre-signed direct-to-S3 upload lifecycle for file-sourced datasets.

MCP Servers 1

Model Context Protocol servers that expose these APIs to AI agents.

adaption-mcp.yml

MCP SERVER

Security Posture 1

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

Adaption Domain Security

TLSv1.2 · DMARC

SECURITY

Resources

Get Started 4

Portal, sign-up, and the first successful call

DeveloperPortal
DeveloperPortal
 GettingStarted
GettingStarted
 SignUp
SignUp
 Login
Login

Documentation 2

Reference material describing how the API behaves

Documentation
Documentation
 APIReference
APIReference

Agent Surfaces 4

MCP servers, agent skills, and machine-readable catalogs

MCPServer
MCPServer
 LLMsTxt
LLMsTxt
 AgentSkill
AgentSkill
 WellKnown
WellKnown

Design & Contract 6

Pagination, idempotency, versioning, errors, and events

Idempotency
Idempotency
 Conventions
Conventions
 ErrorCatalog
ErrorCatalog
 Lifecycle
Lifecycle
 Conformance
Conformance
 DataModel
DataModel

Build 2

SDKs, sample code, and the tooling you integrate with

SDKs
SDKs
 Packages
Packages

Access & Security 2

Authentication, authorization, and security posture

DomainSecurity
DomainSecurity
 Authentication
Authentication

Operate 1

Status, limits, changes, and where to get help

Support
Support

Commercial 2

Pricing, plans, and the legal terms of use

TermsOfService
TermsOfService
 PrivacyPolicy
PrivacyPolicy

Company 1

The organization behind the API

Blog
Blog

Source (apis.yml)

apis.yml Raw ↑ 
aid: adaption
name: Adaption
description: Adaption (Adaption Labs) is a San Francisco AI research company building adaptive, continuously-learning AI systems
  rather than relying on ever-larger static models. Founded in 2026 by former Cohere leaders Sara Hooker and Sudip Roy, it
  exited stealth with a $50M seed round led by Emergence Capital. Its first product, Adaptive Data, exposes a REST API and
  official Python SDK to ingest, adapt, evaluate, and export model-ready training datasets — folding data-optimization techniques
  usually reserved for frontier labs into a self-serve workflow for everyday teams.
url: https://raw.githubusercontent.com/api-evangelist/adaption/refs/heads/main/apis.yml
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source: []
  generated: '2026-07-22'
  method: derived
image: https://adaptionlabs.ai/opengraph-image.jpg?opengraph-image.28ce77cd.jpg
x-type: company
x-source: vc-portfolio
x-backed-by:
- emergence-capital
x-tier: profiled
x-tier-reason: enriched-from-portfolio-lead
specificationVersion: '0.20'
created: '2026-07-17'
modified: '2026-07-17'
tags:
- Company
- Ai
- Artificial Intelligence
- Machine Learning
- Training Data
- Datasets
- Data Augmentation
- LLM
- Model Training
- Developer Tools
apis:
- aid: adaption:adaption-datasets-api
  name: Adaption Datasets API
  description: Create, list, run, evaluate, download, and publish adaptive datasets.
  humanURL: https://docs.adaptionlabs.ai/
  baseURL: https://api.prod.adaptionlabs.ai
  tags:
  - Datasets
  properties:
  - type: OpenAPI
    url: openapi/adaption-datasets-api-openapi.yml
  - type: Documentation
    url: https://docs.adaptionlabs.ai/
  - type: APIReference
    url: https://docs.adaptionlabs.ai/api
  - type: GettingStarted
    url: https://docs.adaptionlabs.ai/introduction/getting-started
- aid: adaption:adaption-upload-api
  name: Adaption Upload API
  description: Pre-signed direct-to-S3 upload lifecycle for file-sourced datasets.
  humanURL: https://docs.adaptionlabs.ai/
  baseURL: https://api.prod.adaptionlabs.ai
  tags:
  - Upload
  properties:
  - type: OpenAPI
    url: openapi/adaption-upload-api-openapi.yml
  - type: Documentation
    url: https://docs.adaptionlabs.ai/
  - type: APIReference
    url: https://docs.adaptionlabs.ai/api
  - type: GettingStarted
    url: https://docs.adaptionlabs.ai/introduction/getting-started
common:
- type: DomainSecurity
  url: security/adaption-domain-security.yml
- type: DeveloperPortal
  url: https://docs.adaptionlabs.ai/
- type: Documentation
  url: https://docs.adaptionlabs.ai/
- type: APIReference
  url: https://docs.adaptionlabs.ai/api
- type: GettingStarted
  url: https://docs.adaptionlabs.ai/introduction/getting-started
- type: Blog
  url: https://adaptionlabs.ai/blog
- type: SignUp
  url: https://www.adaptionlabs.ai/app/auth
- type: Login
  url: https://www.adaptionlabs.ai/app/auth
- type: Support
  url: https://discord.gg/sHhG8kwVav
- type: TermsOfService
  url: https://adaptionlabs.ai/terms-of-service
- type: PrivacyPolicy
  url: https://adaptionlabs.ai/privacy-policy
- type: SDKs
  url: packages/adaption-packages.yml
- type: Packages
  url: packages/adaption-packages.yml
- type: Idempotency
  url: conventions/adaption-conventions.yml
- type: Conventions
  url: conventions/adaption-conventions.yml
- type: Authentication
  url: authentication/adaption-authentication.yml
- type: ErrorCatalog
  url: errors/adaption-problem-types.yml
- type: Lifecycle
  url: lifecycle/adaption-lifecycle.yml
- type: Conformance
  url: conformance/adaption-conformance.yml
- type: DataModel
  url: data-model/adaption-data-model.yml
- type: MCPServer
  url: mcp/adaption-mcp.yml
- type: LLMsTxt
  url: llms/adaption-llms.txt
- type: AgentSkill
  url: skills/_index.yml
- type: WellKnown
  url: well-known/adaption-well-known.yml
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence