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Learn
Start with a decision your team already reviews.
How Cyclotron learns
Reviewer corrections can help improve future AI decisions when a team evaluates the proposed change.
Publish or reject. Escalate or close. Include or leave out. Cyclotron records a reviewer correction, tests a proposed change, and uses accepted evidence to guide later decisions.
This recorded editorial example starts with a story and a publish-or-reject decision. An editor checks it. The correction stays visible, so the next version can be evaluated instead of assumed better.
See how it worksExplore the loop on your own, or see optional services for help integrating and operating it in your product.
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Follow the loop
From an input to a better-informed next decision.
1
Give the model one jobFor each item, make a focused, inspectable call such as publish or reject. Keep the input and decision visible.2
Let a person correct itWhen a reviewer disagrees, the correction records the standard in use. A correction is evidence, not an automatic improvement.3
Evaluate before less reviewTest a proposed change on held-out, representative examples. Agree which errors still need people.
Go deeper
Choose the next question for your task.
Once you see the loop, use these guides to understand a decision model, inspect its evidence, compare models and cost, or plan ongoing review.
Understand
Evaluate
Evaluate
Set up
Operate
See the decisions in practice on the use cases page. Each one says how we know.
Research and evidence
Inspect the evidence behind the guidance.
The research articles explain the experiments behind this guidance, including their methods and limits.
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