Keep your chatbot evaluation record portable

Save the evidence that explains a decision

Keep the approved source inventory, question set, expected answer points, relevant outputs and reviewer rationale. Include dates and version boundaries. A screenshot of an overall score is not enough to reconstruct why a tool passed or failed. The record should let another reviewer understand the decision without access to your memory or a dashboard that may change after cancellation.

Use an ordinary readable format

A table and a small set of text records can be sufficient. Choose a format your team can maintain and export without requiring a new paid tool. Avoid a complicated internal framework unless the scale genuinely requires it. Document field meanings, especially status values such as held or unsupported, so an exported record does not lose its interpretation when a new owner reads it.

Minimize sensitive material

Use synthetic or sanitized evaluation cases wherever possible. Do not preserve passwords, access tokens or unnecessary customer details in the name of reproducibility. Keep references to protected evidence under the organization’s existing access controls rather than copying it into a public worksheet. Portability should not create a second uncontrolled data store. This guide offers an operational pattern, not a substitute for your retention obligations.

Test the exit before depending on it

Before a broader rollout, confirm which source lists, conversation records and settings the product actually lets you export. Record any gaps and the manual evidence you must retain. Do not assume that a feature named export includes every object needed for a migration. A modest portable evaluation record makes a later switch more informed even when the original product remains the best choice.

• Verify that a second person can locate the expected source and interpret one held case using only the exported record and its field notes.