AI System for Preparing Content Rights Documents for Review

The problem

In day-to-day operations, licence agreements, content records and usage requests arrive through different systems and incident records, preventing the team from viewing the case on a single timeline.

As a result, source links may be lost while the summary of rights, territories and terms is prepared, the case may be referred to the wrong team, and the basis for a technical decision may be unclear.

An incomplete workflow may overlook an incomplete chain of rights or conflicting agreements; poorly designed automation creates a risk of unauthorised publication or failure to exercise valid rights.

What we set out to improve

• Time taken for the draft summary of rights, territories and terms to be ready for specialist review
• Correct referral of records involving an incomplete chain of rights or conflicting agreements to the appropriate specialist queue
• Recording of suggestions corrected or rejected by the content rights specialist

How the system works

1. 01 Retrieve licence agreement, content record and usage request data from authorised sources
2. 02 Verify the source, timestamp and record identifier
3. 03 Add the relevant asset, user, location, vehicle or content context
4. 04 Prepare the draft summary of rights, territories and terms
5. 05 Compare the draft with technical rules and authority limits
6. 06 Check for exceptions: an incomplete chain of rights or conflicting agreements
7. 07 Have the content rights specialist approve, correct or reject the draft
8. 08 Write the input, suggestion, changes and final decision to the audit log

Methods we used

• Data extraction with source and timestamp traceability from licence agreements, content records and usage requests
• Structured output that restricts the summary of rights, territories and terms to fields defined by technical rules
• An exception gate that separates an incomplete chain of rights or conflicting agreements from system processing
• An authorised queue that shows the content rights specialist the evidence alongside the suggestion
• Duplicate-processing controls and a reversal record to mitigate the risk of unauthorised publication or failure to exercise valid rights

Where people stay involved

Data and security

Only fields required for the task are processed from licence agreements, content records and usage requests. Source-system permissions are preserved, and unnecessary personal, technical and security-sensitive data is minimised before being provided to the model. Every retrieval, suggestion, human change and target-system action is written to the audit log.

Who this suits

Frequently asked questions