hypothesis-tracking

To manage research hypotheses for a company, use save_hypothesis to create records with evidence trails, then retrieve or update them as new evidence arrives. Confidence levels span a four-stage lifecycle: untested, validated, invalidated, and confirmed.

A four-level confidence system categorizes research validation into untested, validated, invalidated, and confirmed states. It tracks the lifecycle of company hypotheses while maintaining evidence trails and applying expiration rules per topic.

Update an existing company hypothesis by calling save_hypothesis with new evidence. The system enforces unique IDs per company, handles expiration rules across topics, and adjusts the confidence level accordingly.

Yes, the hypothesis tracking system enforces unique IDs per company and provides built-in error handling for missing records and duplicates. This ensures data integrity when retrieving, updating, or creating research entries.

Yes, you can set expiration rules for research hypotheses across different topics. The system manages these expiration parameters per topic, ensuring outdated company knowledge is flagged appropriately during validation.

Manage knowledge validation for multiple companies by enforcing unique IDs per organization. The system's error handling prevents duplicates and manages missing records, while tracking confidence levels and expiration rules per topic.