Stopping Post-Deploy Regressions Before 
They Hurt Customers

Shipping fast shouldn’t mean finding out what broke from your customers.

Yet post-deploy regressions are still one of the hardest problems teams face in production, often detected late, difficult to explain, and time-consuming to fix. As systems grow more complex and deploys happen more frequently, understanding what actually changed becomes the bottleneck.

In this webinar, we’ll show how teams are using AI to make regressions visible the moment they appear, connect them directly to the changes that caused them, and replace guesswork with clear, explainable insight.

Using real production examples, we’ll explore how teams:

• Detect regressions immediately after a deployment, before customers notice
• Understand what changed and why by linking code, runtime behavior, and production signals
• Move from reactive firefighting to confident, predictable releases

If post-deploy surprises, slow investigations, or unclear release impact sound familiar, this session will give you a practical blueprint for stopping regressions early, without slowing down delivery.