Prior Labs website screenshot

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.

🌐 Visit website 📡 Source on GitHub
43.8/100 developing ▬ flat Agent 38/100 agent ready saas Full breakdown ↓
scored 2026-09-08 · rubric v0.20.0
1 APIs 1 MCP Servers
CompanyMachine-LearningArtificial IntelligenceTabular DataFoundation ModelsPredictionsData ScienceMCPSDK

Kin Score

Kin Score Kin Score How this is scored →
scored 2026-09-08 · rubric v0.20.0
Composite quality — 43.8/100 · developing
Contract Quality 13.9 / 23
Developer Ergonomics 11.9 / 18
Access Clarity 3.8 / 18
Operational Transparency 3.1 / 12
Contract Governance 0.5 / 11
Discoverability 6.8 / 9
Create-or-Update Ergonomics 0.0 / 10
Agent readiness — 38/100 · agent ready
Machine-Readable Contract 18 / 18
Agentic Access Contract 10 / 10
Documented Reversibility 0 / 6
MCP Server 12 / 12
Machine-Readable Auth 10 / 10
Idempotency 0 / 9
Stable Error Semantics 8 / 8
Request/Response Examples 7 / 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/priorlabs: 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.

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.

Open Collections 3

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

API Collection

OPEN COLLECTION

TabPFN Prediction API

OPEN COLLECTION

TabPFN Prediction Training API

OPEN COLLECTION

MCP Servers 1

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

Prior Labs MCP Server

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

DeveloperPortal
DeveloperPortal
 GettingStarted
GettingStarted
 SignUp
SignUp

Documentation 3

Reference material describing how the API behaves

Documentation
Documentation
 APIReference
APIReference
 OpenAPI
OpenAPI

Agent Surfaces 4

MCP servers, agent skills, and machine-readable catalogs

MCPServer
MCPServer
 LLMsTxt
LLMsTxt
 AgentSkill
AgentSkill
 AgenticAccess
AgenticAccess

Design & Contract 5

Pagination, idempotency, versioning, errors, and events

Conventions
Conventions
 ErrorCatalog
ErrorCatalog
 Lifecycle
Lifecycle
 DataModel
DataModel
 Conformance
Conformance

Build 3

SDKs, sample code, and the tooling you integrate with

GitHubOrganization
GitHubOrganization
 Packages
Packages
 SDKs
SDKs

Access & Security 2

Authentication, authorization, and security posture

Authentication
Authentication
 DomainSecurity
DomainSecurity

Operate 3

Status, limits, changes, and where to get help

Support
Support
 ChangeLog
ChangeLog
 Deprecation
Deprecation

Commercial 2

Pricing, plans, and the legal terms of use

TermsOfService
TermsOfService
 PrivacyPolicy
PrivacyPolicy

Company 2

The organization behind the API

Blog
Blog
 Website
Website

Other 1

Properties that don't map to a standard resource type

Overlay
Overlay

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
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://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: '0.23'
created: '2026-07-17'
modified: '2026-07-20'
tags:
- Company
- Machine-Learning
- Artificial Intelligence
- Tabular Data
- Foundation Models
- Predictions
- Data Science
- MCP
- SDK
tags_raw:
- 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/_original/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

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