Tecton overview
Transform. Serve. Scale.

Feature Platform for Real-Time Machine Learning

Power all your models with production-ready batch, streaming, and real-time data pipelines

Tecton overview

From the creators of Uber Michelangelo, the ML Platform powering every model at Uber. Tecton is trusted by leading ML teams.

More than just a feature store

The All-in-one System to Build, Automate, and Centralize Feature Workflows for Production ML

Production Pipelines in Minutes

Create robust data pipelines from just a few lines of code — Tecton automatically builds, orchestrates, and maintains them so your teams don’t have to

Increased Model Accuracy

Automate robust pipelines that materialize fresh features consistently across training and serving environments to ensure improved model performance

Improved Collaboration

Standardize machine learning data workflows in one platform so teams can easily share and reuse features across use cases

Mission-Critical Reliability

Serve features in production at extreme scale  for batch, streaming, or real-time ML with the confidence that systems will always be up and running

The problem we solve
The problem we solve

Data Engineering for Real-Time ML Is Hard

A complete platform

Design and Manage the Entire ML Feature Lifecycle

From simple declarative transformation logic to fresh feature values you can store, serve, and monitor, in real-time.

Feature Management: Discover, Use, Monitor, and Govern End-to-end Feature Pipelines

With Tecton, anyone on the team can discover and use existing features all the while monitoring associated data pipelines, serving latencies, processing costs, and underlying systems of their machine learning applications.

Feature Logic: Design and Define ML Features

By using the SDK in a notebook or any other Python environment, users can define feature logic in SQL, PySpark, SnowPark, or Python, and rely on Tecton to execute complex data transformations like time-window aggregations or generate training data with accurate backfills.

Feature Repository: Register and Collaborate on Feature Definitions

Tecton’s feature repository lets users manage feature definitions as files in a git-like repository. With Tecton, users define features in code, version control them in git, unit test them, and roll them out safely using Continuous Delivery pipelines. With Tecton, bring battle-tested DevOps software practices to feature engineering.

Feature Engine: Transform Raw Data Into Fresh Feature Values

Tecton integrates with existing data processing and storage infrastructures to automatically compile the underlying data pipelines that compute batch, streaming, or real-time features, insulating the end user from their complexity.

Feature Store: Store and Serve Fresh Feature Values

Based on a user’s pre-defined requirements, Tecton helps organizations scale compute, storage, and serving independently to adjust to usage patterns, leverages an offline store for large-scale and low-cost retrieval (training) and an online store for low-latency retrieval (online serving). Tecton provides uninterrupted access to fresh features on demand.

Customer Stories

Hear Cash App’s journey through various generations of its core machine-learning capabilities and how Tecton’s real-time feature platform helps them deliver world-class recommendations.
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Atlassian reduced the time to deploy new features from 1-3 months to 1 day using Tecton, powering recommendations in Jira and Confluence.
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Tide used Tecton to launch automatic fraud detection during new customer onboarding, replacing manual reviews of new accounts and saving $600K.
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Battle tested for the enterprise

Reliability and Scale You Expect From a Production System

Fully Managed and Cloud Native

Tecton makes it easy to deploy and operate machine learning with a managed, cloud native service.

Built for Availability and Scale

Tecton is built for scale, delivering median latencies of ~5ms and supporting over 100,000 of requests per second.

Integrates with Your Existing Stack

Tecton is not a database or a processing engine. It plugs into and orchestrates on top of your existing storage and processing infrastructure.

Secure and Compliant

Tecton authenticates users via SSO and includes support for access control lists. We support GDPR compliance in your ML applications, and are SOC2 Type 2 certified.


Build Features, Not Pipelines

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