Prior Labs

Prior Labs builds TabPFN, a tabular foundation model that delivers strong predictions on structured/tabular data in seconds — no dataset-specific training, tuning, or ML pipelines required. TabPFN-3 handles classification, regression, time-series forecasting, anomaly detection, synthetic data generation, embeddings, and uncertainty quantification via in-context learning, scaling to 1M rows, 2,000 columns, and 160 classes. Prior Labs exposes TabPFN through a cloud REST API (api.priorlabs.ai), Python and R client SDKs, a Model Context Protocol server for AI agents, and private deployments on AWS SageMaker, Databricks, and Azure AI Foundry. The company was published in Nature and is now part of SAP.

Prior Labs publishes 2 APIs on the APIs.io network: Prediction API and Training API. Tagged areas include Company, Machine Learning, Artificial Intelligence, Tabular Data, and Foundation Models.

Prior Labs’ developer surface includes documentation, API reference, getting-started guide, engineering blog, signup flow, support, changelog, and 21 more developer resources.

50.6/100 developing ▬ flat Agent 65/100 agent native Full breakdown ↓
scored 2026-07-23 · rubric v0.5
AccessSelf serve
2 APIs 1 MCP Servers
CompanyMachine LearningArtificial IntelligenceTabular DataFoundation ModelsPredictionsData ScienceMCPSDK

Kin Score

Kin Score Kin Score How this is scored →
scored 2026-07-23 · rubric v0.5
Composite quality — 50.6/100 · developing
Contract Quality 15.9 / 25
Developer Ergonomics 14.8 / 20
Commercial Clarity 6.8 / 20
Operational Transparency 3.8 / 13
Governance 0.0 / 12
Discoverability 9.3 / 10
Agent readiness — 65/100 · agent native
Machine-Readable Contract 18 / 18
Agentic Access Contract 15 / 15
MCP Server 12 / 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
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/priorlabs: 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.

Prior Labs Prediction API

The Prediction API from Prior Labs — 3 operation(s) for prediction.

Prior Labs Training API

The Training API from Prior Labs — 4 operation(s) for training.

MCP Servers 1

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

priorlabs-mcp.yml

MCP SERVER

Security Posture 2

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

Priorlabs Authentication

http · 1 scheme

SECURITY

Priorlabs Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Agentic Access 1

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

Priorlabs Agentic Access

7 operations · 6 acting

7 operations · 6 acting

AGENTIC

Resources

Get Started 3

Portal, sign-up, and the first successful call

Documentation 3

Reference material describing how the API behaves

Agent Surfaces 4

MCP servers, agent skills, and machine-readable catalogs

Design & Contract 5

Pagination, idempotency, versioning, errors, and events

Build 3

SDKs, sample code, and the tooling you integrate with

Access & Security 2

Authentication, authorization, and security posture

Operate 3

Status, limits, changes, and where to get help

Commercial 2

Pricing, plans, and the legal terms of use

Company 2

The organization behind the API

Other 1

Properties that don't map to a standard resource type

Source (apis.yml)

apis.yml Raw ↑
aid: priorlabs
name: Prior Labs
description: Prior Labs builds TabPFN, a tabular foundation model that delivers strong predictions on structured/tabular data
  in seconds — no dataset-specific training, tuning, or ML pipelines required. TabPFN-3 handles classification, regression,
  time-series forecasting, anomaly detection, synthetic data generation, embeddings, and uncertainty quantification via in-context
  learning, scaling to 1M rows, 2,000 columns, and 160 classes. Prior Labs exposes TabPFN through a cloud REST API (api.priorlabs.ai),
  Python and R client SDKs, a Model Context Protocol server for AI agents, and private deployments on AWS SageMaker, Databricks,
  and Azure AI Foundry. The company was published in Nature and is now part of SAP.
url: https://raw.githubusercontent.com/api-evangelist/priorlabs/refs/heads/main/apis.yml
accessModel:
  pricing: unknown
  onboarding: self-serve
  trial: false
  try_now: false
  public: false
  label: Self-serve signup
  confidence: medium
  source:
  - authentication
  generated: '2026-07-22'
  method: derived
image: https://priorlabs.ai/pl.svg
x-type: company
x-source: vc-portfolio
x-backed-by:
- balderton-capital
x-tier: stub
x-tier-reason: portfolio-lead
specificationVersion: '0.20'
created: '2026-07-17'
modified: '2026-07-20'
tags:
- Company
- Machine Learning
- Artificial Intelligence
- Tabular Data
- Foundation Models
- Predictions
- Data Science
- MCP
- SDK
apis:
- aid: priorlabs:priorlabs-prediction-api
  name: Prior Labs Prediction API
  description: The Prediction API from Prior Labs — 3 operation(s) for prediction.
  humanURL: https://docs.priorlabs.ai/api-reference/getting-started
  baseURL: https://api.priorlabs.ai
  tags:
  - Prediction
  properties:
  - type: OpenAPI
    url: openapi/priorlabs-prediction-api-openapi.yml
  - type: APIReference
    url: https://docs.priorlabs.ai/api-reference/getting-started
- aid: priorlabs:priorlabs-training-api
  name: Prior Labs Training API
  description: The Training API from Prior Labs — 4 operation(s) for training.
  humanURL: https://docs.priorlabs.ai/api-reference/getting-started
  baseURL: https://api.priorlabs.ai
  tags:
  - Training
  properties:
  - type: OpenAPI
    url: openapi/priorlabs-training-api-openapi.yml
  - type: APIReference
    url: https://docs.priorlabs.ai/api-reference/getting-started
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Documentation
  url: https://docs.priorlabs.ai/overview
- type: DeveloperPortal
  url: https://docs.priorlabs.ai/
- type: APIReference
  url: https://docs.priorlabs.ai/api-reference/getting-started
- type: GettingStarted
  url: https://docs.priorlabs.ai/quickstart
- type: Blog
  url: https://priorlabs.ai/blog
- type: GitHubOrganization
  url: https://github.com/PriorLabs
- type: SignUp
  url: https://ux.priorlabs.ai/home
- type: TermsOfService
  url: https://priorlabs.ai/terms
- type: PrivacyPolicy
  url: https://priorlabs.ai/privacy-policy
- type: Support
  url: mailto:hello@priorlabs.ai
- type: ChangeLog
  url: https://docs.priorlabs.ai/changelog
- type: OpenAPI
  url: openapi/priorlabs-openapi-original.json
- type: Overlay
  url: overlays/priorlabs-tabpfn-overlay.yaml
- type: MCPServer
  url: mcp/priorlabs-mcp.yml
- type: LLMsTxt
  url: llms/priorlabs-llms.txt
- type: Packages
  url: packages/priorlabs-packages.yml
- type: SDKs
  url: packages/priorlabs-packages.yml
- type: AgentSkill
  url: skills/_index.yml
- type: Authentication
  url: authentication/priorlabs-authentication.yml
- type: Conventions
  url: conventions/priorlabs-conventions.yml
- type: ErrorCatalog
  url: errors/priorlabs-problem-types.yml
- type: Lifecycle
  url: lifecycle/priorlabs-lifecycle.yml
- type: Deprecation
  url: lifecycle/priorlabs-lifecycle.yml
- type: DataModel
  url: data-model/priorlabs-data-model.yml
- type: Conformance
  url: conformance/priorlabs-conformance.yml
- type: AgenticAccess
  url: agentic-access/priorlabs-agentic-access.yml
- type: DomainSecurity
  url: security/priorlabs-domain-security.yml
- type: Website
  url: https://priorlabs.ai/
x-enrichment:
  date: '2026-07-20'
  status: enriched
  artifacts_added: 17
  pass: local-v1