Why AI Needs Better Context

November 7, 2024

As companies increasingly rely on AI to drive personalized, real-time decisions, the need for robust, fresh context has never been greater. When models shift from development to production, however, they often fail to perform as expected, leading to …

Navigating the MLOps Landscape: 4 Key Insights From apply(ops)

December 19, 2023

Check out this blog post for the 4 major takeaways from apply(ops), which featured talks from Uber, HelloFresh, Riot Games, and more.

How Plaid Uses Tecton to Detect and Prevent Fraud

November 9, 2023

Learn how Plaid built Signal, an ML platform that powers payment fraud detection and prevention, in this post.

What Is Operational Machine Learning?

May 26, 2022

In this post, Kevin Stumpf, CTO of Tecton, describes what operational ML really is and gives practical examples to understand how it works.

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 …