Building a Feature Store

January 20, 2022

As more and more teams seek to institutionalize machine learning, we’ve seen a huge rise in ML Platform Teams who are responsible for building or buying the tools needed to enable practitioners to efficiently build production ML systems. Almost …

2021 at Tecton: A Year in Review

December 29, 2021

2021 is a wrap, and what a year it has been! As we head into the New Year, I want to take a look back at what we’ve accomplished this year and share with you some of the things I expect for 2022. Tecton has experienced a huge amount of growth this …

Journey to Real-Time Machine Learning

August 9, 2021

We speak with hundreds of enterprise machine learning teams every year. And we’ve observed a typical pattern for the adoption of machine learning in the enterprise. Not every organization follows the exact same steps, but we’ve seen the pattern …

Data Software-as-a-Service: The Case for a Hybrid Deployment Architecture

March 17, 2021

Lior Gavish & Kevin Stumpf As founders of companies that build solutions designed to help teams deliver on the promise of data, we knew we wanted to build great products that are easy to deploy and manage for our customers.  We also knew …

Back to the Future: Solving the time-travel problem in machine learning

July 6, 2020

In Back to the Future II, Marty McFly gets an idea to purchase a sports almanac in the future and bring it back to the past to use for betting. Doc Brown warns him not to profit from time travel because information from the future could create …

Why We Need DevOps for ML Data

April 28, 2020

Getting machine learning (ML) into production is hard. In fact, it’s possibly an order of magnitude harder than getting traditional software deployed. As a result, most ML projects never see the light of production-day and many organizations simply …