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Agent-driven experimentation

Self Improving Apps.

Cycle automatically finds, ships, and measures experiments designed to increase signups, retention, revenue, or whatever matters most to you.

See how it works
A precision plotter drawing a series of evolving paths
From product signal to shipped experiment to learning

How it works

01

Discover

Agents analyze your product and propose the highest-potential experiments to run next.

02

Ship

AI makes the update and releases it safely behind a feature flag.

03

Learn

Cycle measures the outcome, explains what changed, and starts the next experiment.

The Cycle platform

One continuous loop from insight to impact.

Set the outcome that matters. Cycle's agents handle the work of finding an opportunity, shipping an experiment, and learning from the result.

Opportunity discovery01 / 03

Always know what to test next.

Cycle's agents turn product signals and business goals into ranked, testable ideas, each with a clear reason to run.

  • AI-suggested experiments grounded in product signals
  • Clear hypotheses, target metrics, and guardrails
  • Prioritized by expected impact and effort
Safe execution02 / 03

Go from idea to live experiment.

Agents prepare the product update, connect it to a feature flag, and help you control who sees it and when.

  • Agent-made product updates
  • Targeted rollouts and controlled rollback
  • Review controls for every experiment
Closed-loop learning03 / 03

Turn every result into the next move.

Cycle watches the metrics that matter, explains what changed, and carries the evidence into the next cycle.

  • Analysis performed by AI agents
  • Primary outcomes and guardrails in one view
  • Winners promoted and learnings retained

Designed for continuous improvement

Autonomous where it helps. Controlled where it matters.

Optimize for your outcome

Define what matters, from activation and retention to revenue. Every cycle stays tied to that result.

Ship safely, learn quickly

Treatments run behind feature flags with targeted exposure, guardrails, and a clear rollback path.

Make every experiment compound

Cycle retains the evidence and context so its agents improve what they propose and how they execute.

The self-improving loop

Your product gets better with every cycle.

Cycle connects product signals, code changes, controlled rollouts, and outcome analysis into one agent-driven system.

01

Discover

Agents turn product signals into ranked, measurable experiments.

02

Ship

Agents release the update safely behind feature flags.

03

Learn

Results are analyzed and winning variants can be promoted.

04

Repeat

The evidence shapes the next experiment automatically.

Start with one outcome

What should your app improve next?

Tell Cycle what matters most. Its agents will turn that goal into your next experiment.