Tecton

Tecton's historical Tide case study reports production rollout in six weeks, a 50% reduction in model delivery time, and 20% fewer blocked transactions alongside a fourfold increase in fraud likelihood among blocked transactions.

Tecton powers real-time ML feature infrastructure for major engineering teams including Coinbase, GoDaddy, Progressive, Remitly, Square, HelloFresh and others; joint customers with Databricks have reported tens of millions in business impact.

Tecton powers real-time ML feature infrastructure for major engineering teams including Coinbase, GoDaddy, Progressive, Remitly, Square, HelloFresh and others; joint customers with Databricks have reported tens of millions in business impact.

Tecton pioneered a production feature platform for real-time ML with ultra-low-latency serving, 100ms data freshness and consistency between training and serving.

Tecton pioneered a production feature platform for real-time ML with ultra-low-latency serving, 100ms data freshness and consistency between training and serving.

Databricks documents Tecton point-in-time correctness, historical and real-time feature consistency and a unified data-serving system for AI agents; its architecture supports sub-10ms serving latency, sub-100ms freshness and 99.99 percent uptime.

Databricks describes Tecton as founded by the creators of Uber's AI and ML platform that supported thousands of production models. This adds attributable prior engineering execution experience distinct from the existing acquisition observation.

Tecton was acquired by Databricks in 2025, combining its real-time ML infrastructure and team with a global enterprise data/AI platform.

Tecton was acquired by Databricks in 2025, combining its real-time ML infrastructure and team with a global enterprise data/AI platform.

Tecton documents reusable Feature Services used consistently for online inference and offline training, Python SDK historical feature retrieval and online feature logging for audits and training datasets. These concrete workflows support an inference of portable production-ML data engineering skills.

Feature engineering, real-time data, ML platform, low-latency serving and production ML infrastructure skills transfer exceptionally broadly across AI and data companies.

Feature engineering, real-time data, ML platform, low-latency serving and production ML infrastructure skills transfer exceptionally broadly across AI and data companies.