Tecton

Tecton is a managed feature platform for machine learning teams, built to solve the gap between data science notebooks and production ML systems. It lets teams define features once, then serves them consistently for both offline model training and low-latency online inference, which avoids the classic training/serving skew problem.

Tecton runs on top of a team's existing data warehouse and streaming infrastructure (Snowflake, Databricks, Kafka) rather than replacing it, and integrates with common orchestration and model-serving tools. It is aimed at organizations running real-time ML use cases — fraud detection, recommendation, personalization — where feature freshness and consistency directly affect model accuracy.

Because it is enterprise-priced and requires integration work against a company's existing data stack, Tecton is generally adopted by teams already running ML in production at meaningful scale, not early-stage projects.