AI is shipping features faster than teams can validate them. The old model, deploy to everyone and monitor for fires, doesn't scale when the pace accelerates by 10X.

The fix isn't slowing down. It's separating deploy from release.

Code ships dark. Features turn on deliberately, to the right users, with automated guardrails that roll back without waking anyone up. And every experiment ties directly to the deploy that shipped it, so when something regresses, you know exactly why. When something works you know the impact to the business.

What you'll see

• Feature flags managed inside the same platform as your CD pipeline, no separate tool, no separate access model
• A live controlled rollout: 5% of users, automated kill switch, experiment results in real time
• AI recommending rollout strategies based on your historical experiment data
• OPA flag lifecycle policies that prevent flag debt before it accumulates

Who this is for Product engineers, engineering managers, and product management  teams who want to move faster without exposing every user to every change.