Harness Feature Management & Experimentation

AI-powered agent that explains experiment results and highlights what impacts metrics, providing clear insights and guided next steps.

Receive immediate alerts when a gradual release impacts system performance or user behavior, enabling quick action.

Automatically turn features off if issues are detected during rollout.

Control components of software features without deploying new code, empowering teams to iterate in real-time with minimal risk.

Run A/B tests with self-service tools once experimentation infrastructure is in place through feature flag measurement.

Eliminate fragmented experimentation islands by centralizing experiments to a single source of truth with proven methodology.

Include approvals and audit trails for feature flag changes with integration into CI/CD pipelines as visual workflows.

Enforce explicit flag lifecycle to identify flags ready for retirement based on inactivity metrics and automate cleanup tracking.

Automatically track performance issues and errors caused by each flag the moment a gradual release starts.

Catch release issues most monitoring tools miss by quickly detecting the impact of each individual feature, even with multiple concurrent rollouts.

Get fast feature flag evaluations made locally inside the app without sending private user data to the cloud.

Speed up software delivery by deploying code in production without releasing it to customers. Safely test, target, and turn features on/off with effortless controls.

Enable safe gradual rollouts and canary releases with controlled exposure of new features.

Customize who sees what and when by gradually rolling out features to defined customer sets or conducting beta tests to random samples of users.

Enable safe testing in production by separating code deployment from feature release.