Trust centre
Trust the record by understanding how it was created.
Review public information about data handling, security, AI processing, human verification, retention and providers—without unsupported assurances.
Source visibility
Return to the message and evidence behind a suggested record.
Human verification
A person checks suggestions before relying on operational work.
Correctable output
Owners, dates, wording and status remain reviewable.
Explicit limits
Unverified security and provider claims are not presented as fact.
Trust topics
The questions a project team should ask before enabling AI.
Security claims should be specific, current and verifiable
Review the security controls Convoe can currently describe publicly, along with the claims that require direct confirmation.
Read this topicPrivacy information without hiding the important questions
A plain-language overview of Convoe privacy contacts, analytics consent and the relationship to the full privacy policy.
Read this topicKnow what AI receives before project data is processed
Understand what must be verified before enabling Convoe AI with project data, including providers, retention, training and human review.
Read this topicA processor registry that says what it covers
Review the maintainable registry for processors used by the public Convoe website and request the current product schedule.
Read this topicRetention should follow a documented rule, not a vague promise
Review how retention, export and deletion should be confirmed for Convoe project data and the public website.
Read this topicAn AI suggestion is not a confirmed project record
See the difference between an AI suggestion, human confirmation, source message, edit history and completion evidence.
Read this topicUse AI to reduce re-entry—not to remove responsibility
Convoe responsible-AI principles for human approval, source visibility, correction and clear limits in field workflows.
Read this topicOne site is enough to start
Evaluate the workflow and its controls together.
Book a review to discuss where AI assists, where people confirm and what your team needs to verify before project use.