Feature Platform | Tecton


Feature Platform

The Fastest Way to Build and Deploy Data Pipelines for Machine Learning

Tecton is a fully-managed feature platform built to orchestrate the complete lifecycle of features, from transformation to online serving, with enterprise-grade SLAs.


Explore the Platform

We Built a Feature Platform So You Don’t Have To

Feature Repository

Define and manage features as code

machine learning features in a git repository

Apply changes into Tecton...

…and Tecton will automatically transform, store and serve features

Feature Pipelines


Feature Store


Feature Store




Machine learning serving latency monitoring

Feature Platform

tecton feature library

Govern and Collaborate

Fully Managed and Cloud Native

A Cloud-Native Solution Built for Reliability and Scale

Fully managed service

Let Tecton manage your feature store with guaranteed SLAs and enterprise support out of the box. Tecton is built on best-in-class cloud services to maximize resilience and scale.

Elastic scalability

Tecton optimizes resource utilization and scales dynamically based on your requirements. We scale compute, storage, and serving independently to adjust to your usage patterns.

Cost optimized

Tecton’s core IP implements feature transformations in a cost-effective way, and Tecton is priced on consumption so you only pay for what you use.


Plugs Into Your Existing Infrastructure

Tecton integrates seamlessly with other parts of the ML stack. It connects to existing data processing and storage infrastructure and allows you to use any model training and serving tools you desire.

Connects to your batch and real-time data sources

Tecton provides beautiful abstractions so data scientists don't need to focus on where the data is being sourced from.

Gives you flexibility for compute and storage

Tecton sits on top and orchestrates your existing compute engine to run feature pipelines. It stores features in the platform of your choice.

Integrates seamlessly with a thriving ecosystem

Tecton can cleanly interface with any other machine learning tools that already exist in your organization.

Allows you to develop in the tools you know and love

Tecton allows you to define features using SQL, Pyspark or Python. Use the SDK in a notebook or any other Python environment to do feature engineering and generate training data.

Tecton stands out as one of the most complete enterprise-ready feature store platforms that can be incorporated into any ML infrastructure.

-TheSequence Scope AI Newsletter


A Platform You Can Trust

Tecton’s core principle is reliability. That’s why we’re trusted across Fortune 500 companies.

Scale to any volume

Tecton powers ML applications that are business critical. Develop with the confidence that your ML infrastructure will scale to meet your needs.

High availability and reliability

We operate with best-in-class uptime and the highest enterprise reliability standards.


Tecton is built for scale and can support thousands of models, tens of thousands of features, and millions of predictions per second. You can start small, and Tecton will scale with you.

World class support

Tecton comes with the highest guarantee of support. Manage your mission-critical applications with confidence that you’ll receive world class support around the clock.

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Best-in-class security & compliance

Data for machine learning is subject to the most stringent legal, regulatory, privacy, compliance, and security requirements. Tecton is built to meet those requirements.

Secure by design

Tecton’s deployment model gives you control over your data while benefiting from the agility of a SaaS solution. Tecton integrates with your SSO, provides comprehensive access controls, and builds on AWS-standard encryption and IAM permissions.

SOC2 Type 2 compliance

Tecton is SOC 2 Type 2 compliant, with best-in-class controls for privacy and data management.

Enables GDPR compliance

Tecton allows organizations to comply with the right to be forgotten, enabling your ML applications to be GDPR compliant.


Build Features, Not Pipelines

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