Tecton website screenshot

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.

🌐 Visit website 📡 Source on GitHub
26.1/100 emerging ▬ flat Agent 3/100 human only library Full breakdown ↓
scored 2026-09-08 · rubric v0.20.0
1 APIs
CompanyMachine-LearningFeature StoreFeature PlatformMLOpsArtificial IntelligenceReal-Time DataSDK

Kin Score

Kin Score Kin Score How this is scored →
scored 2026-09-08 · rubric v0.20.0
Composite quality — 26.1/100 · emerging
Contract Quality 0.0 / 25
Developer Ergonomics 11.4 / 20
Access Clarity 3.2 / 20
Operational Transparency 3.4 / 13
Contract Governance 0.5 / 12
Discoverability 7.6 / 10
Agent readiness — 3/100 · human only
Machine-Readable Contract 0 / 18
Agentic Access Contract 0 / 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 0 / 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
Create-or-Update Ergonomics could not be measured. We hold no machine-readable contract for this provider to read, so there is nothing to measure a write surface against. Excluded rather than scored zero: never-measured and measured-empty are different facts. Publishing an OpenAPI is what makes this facet — and several others — scorable at all.
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/tecton: 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 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...

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

DeveloperPortal
DeveloperPortal
 GettingStarted
GettingStarted

Documentation 2

Reference material describing how the API behaves

Documentation
Documentation
 APIReference
APIReference

Agent Surfaces 2

MCP servers, agent skills, and machine-readable catalogs

X-MCPServerCandidate
X-MCPServerCandidate
 LLMsTxt
LLMsTxt

Design & Contract 4

Pagination, idempotency, versioning, errors, and events

Conventions
Conventions
 Conformance
Conformance
 Lifecycle
Lifecycle
 DataModel
DataModel

Build 4

SDKs, sample code, and the tooling you integrate with

GitHubOrganization
GitHubOrganization
 Packages
Packages
 SDKs
SDKs
 CLI
CLI

Access & Security 4

Authentication, authorization, and security posture

Compliance
Compliance
 TrustCenter
TrustCenter
 DomainSecurity
DomainSecurity
 Authentication
Authentication

Operate 2

Status, limits, changes, and where to get help

StatusPage
StatusPage
 Deprecation
Deprecation

Company 1

The organization behind the API

Website
Website

Source (apis.yml)

apis.yml Raw ↑ 
aid: tecton
deliveryModel:
  model: library
  open_source: false
  commercial: false
  callable_host: false
  label: Library · distributed through package registries, no callable service
  confidence: low
  source:
  - none
  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
  - url: https://www.tecton.ai
    status: 301
    note: declared website redirects to https://www.databricks.com/ — a different registrable domain (tecton.ai -> databricks.com),
      possible rename or acquisition (probed 2026-09-03, roadmap#169)
  generated: '2026-09-03'
  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: '0.23'
created: '2026-07-17'
modified: '2026-07-21'
tags:
- Company
- Machine-Learning
- Feature Store
- Feature Platform
- MLOps
- Artificial Intelligence
- Real-Time Data
- SDK
tags_raw:
- 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: X-MCPServerCandidate
  url: mcp/tecton-mcp.yml
  note: 'Renamed from MCPServer 2026-09-03 (roadmap#247): the manifest self-describes as status: candidate — a tool list derived
    from the published API contracts, not an existing server. The scorer already read the manifest and reported mcp_server
    correctly; the MCPServer type was crediting the artifact-type surfaces with a server that does not exist.'
- type: LLMsTxt
  url: llms/tecton-llms.txt
x-enrichment:
  date: '2026-07-21'
  status: enriched
  artifacts_added: 12
  pass: local-v1

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