Tecton

Tecton is the enterprise feature platform (feature store) for real-time machine learning and AI at scale. It transforms raw batch, streaming, and real-time data into ML-ready features and embeddings, orchestrates the pipelines that materialize them, and serves them to models online with low latency and ~100ms freshness while guaranteeing training/serving consistency. Developers define features as code with the Python SDK and `tecton` CLI, then read them for inference through the FeatureService HTTP API and open-source Python and Java client libraries. Backed by Andreessen Horowitz, Lux Capital, and SV Angel.

Tecton publishes 1 API on the APIs.io network. Tagged areas include Company, Machine Learning, Feature Store, Feature Platform, and MLOps.

Tecton’s developer surface includes documentation, API reference, getting-started guide, authentication, CLI, and 16 more developer resources.

29.6/100 emerging ▬ flat Agent 21/100 agent aware Full breakdown ↓
scored 2026-07-27 · rubric v0.5
AccessSelf serve
1 APIs 1 MCP Servers
CompanyMachine LearningFeature StoreFeature PlatformMLOpsArtificial IntelligenceReal-Time DataSDK

Kin Score

Kin Score Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5
Composite quality — 29.6/100 · emerging
Contract Quality 0.0 / 25
Developer Ergonomics 13.5 / 20
Commercial Clarity 3.2 / 20
Operational Transparency 3.8 / 13
Governance 0.0 / 12
Discoverability 9.3 / 10
Agent readiness — 21/100 · agent aware
Machine-Readable Contract 0 / 18
Agentic Access Contract 0 / 15
MCP Server 12 / 12
Machine-Readable Auth 10 / 10
Idempotency 0 / 9
Stable Error Semantics 0 / 8
Request/Response Examples 0 / 7
Rate-Limit Signaling 0 / 7
Typed Event Surface 0 / 6
Agent Skills 0 / 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/tecton: 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 1

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

Tecton FeatureService HTTP API

Low-latency online feature serving for model inference — read single or batched feature vectors, wildcard queries, and feature-service metadata. Authenticated with an Authorizat...

MCP Servers 1

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

tecton-mcp.yml

MCP SERVER

Security Posture 3

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

Tecton Authentication

apiKey · 2 schemes

SECURITY

Tecton Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Tecton Trust Center

SOC 2, ISO 27001, GDPR

SECURITY

Resources

Get Started 2

Portal, sign-up, and the first successful call

Documentation 2

Reference material describing how the API behaves

Agent Surfaces 2

MCP servers, agent skills, and machine-readable catalogs

Design & Contract 4

Pagination, idempotency, versioning, errors, and events

Build 4

SDKs, sample code, and the tooling you integrate with

Access & Security 4

Authentication, authorization, and security posture

Operate 2

Status, limits, changes, and where to get help

Company 1

The organization behind the API

Source (apis.yml)

apis.yml Raw ↑
aid: tecton
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://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/tecton.png
name: Tecton
description: Tecton is the enterprise feature platform (feature store) for real-time machine learning and AI at scale. It
  transforms raw batch, streaming, and real-time data into ML-ready features and embeddings, orchestrates the pipelines that
  materialize them, and serves them to models online with low latency and ~100ms freshness while guaranteeing training/serving
  consistency. Developers define features as code with the Python SDK and `tecton` CLI, then read them for inference through
  the FeatureService HTTP API and open-source Python and Java client libraries. Backed by Andreessen Horowitz, Lux Capital,
  and SV Angel.
url: https://raw.githubusercontent.com/api-evangelist/tecton/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- a16z
- lux-capital
- sv-angel
x-tier: stub
x-tier-reason: portfolio-lead
specificationVersion: '0.20'
created: '2026-07-17'
modified: '2026-07-21'
tags:
- Company
- Machine Learning
- Feature Store
- Feature Platform
- MLOps
- Artificial Intelligence
- Real-Time Data
- SDK
apis:
- name: Tecton FeatureService HTTP API
  description: Low-latency online feature serving for model inference — read single or batched feature vectors, wildcard queries,
    and feature-service metadata. Authenticated with an Authorization Tecton-key header bound to a Service Account. Served
    from customer-specific cluster domains (https://<customer-cluster>.tecton.ai/api/v1/...).
  humanURL: https://docs.tecton.ai/docs/reading-feature-data/reading-online-features-for-inference-using-the-http-api
  baseURL: https://docs.tecton.ai
  properties:
  - type: Documentation
    url: https://docs.tecton.ai/docs/reading-feature-data/reading-online-features-for-inference-using-the-http-api
  - type: Authentication
    url: authentication/tecton-authentication.yml
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Website
  url: https://www.tecton.ai
- type: DeveloperPortal
  url: https://docs.tecton.ai
- type: Documentation
  url: https://docs.tecton.ai
- type: APIReference
  url: https://docs.tecton.ai/docs/reading-feature-data/reading-online-features-for-inference-using-the-http-api
- type: GettingStarted
  url: https://docs.tecton.ai/docs/tutorials/tecton-quick-start
- type: GitHubOrganization
  url: https://github.com/tecton-ai
- type: StatusPage
  url: https://tecton.statuspage.io
- type: Compliance
  url: https://docs.tecton.ai/docs/security
- type: TrustCenter
  url: security/tecton-trust-center.yml
- type: DomainSecurity
  url: security/tecton-domain-security.yml
- type: Authentication
  url: authentication/tecton-authentication.yml
- type: Packages
  url: packages/tecton-packages.yml
- type: SDKs
  url: packages/tecton-packages.yml
- type: CLI
  url: cli/tecton-cli.yml
- type: Conventions
  url: conventions/tecton-conventions.yml
- type: Conformance
  url: conformance/tecton-conformance.yml
- type: Lifecycle
  url: lifecycle/tecton-lifecycle.yml
- type: Deprecation
  url: lifecycle/tecton-lifecycle.yml
- type: DataModel
  url: data-model/tecton-data-model.yml
- type: MCPServer
  url: mcp/tecton-mcp.yml
- type: LLMsTxt
  url: llms/tecton-llms.txt
x-enrichment:
  date: '2026-07-21'
  status: enriched
  artifacts_added: 12
  pass: local-v1