AI System for Preparing Backup Incidents for Recovery Review

The problem

In day-to-day operations, backup jobs, error logs and retention policies arrive through different systems and event records, preventing the team from seeing the case on a single timeline.

As a result, source links can be lost while the failure summary and action queue are prepared, the case can be routed to the wrong team, and the basis for the technical decision can remain unclear.

An incomplete workflow may overlook a critical system or missing verification test, while an incorrect system action could lead the team to rely on an unusable backup that appears successful.

What we set out to improve

• Time taken for the draft failure summary and action queue to be ready for specialist review
• Correct referral of records involving a critical system or missing verification test to the appropriate specialist queue
• Record of recommendations corrected or rejected by the backup lead

How the system works

1. 01 Retrieve backup jobs, error logs and retention policies from authorised sources
2. 02 Verify the source, timestamp and record identifier
3. 03 Add the relevant asset, user, shop, vehicle or content context
4. 04 Prepare a draft failure summary and action queue
5. 05 Compare the draft with technical rules and authority boundaries
6. 06 Check for exceptions: a critical system or missing verification test
7. 07 Obtain the backup lead's approval, correction or rejection
8. 08 Write the input, recommendation, changes and final decision to the audit log

Methods we used

• Source- and time-traceable data extraction for backup jobs, error logs and retention policies
• Structured output that restricts the failure summary and action queue fields to technical rules
• An exception gate that separates cases involving a critical system or missing verification test from system action
• An authorised queue that presents the evidence and recommendation together for the backup lead
• Duplicate-processing controls and a rollback record to address the risk of relying on an unusable backup that appears successful

Where people stay involved

Data and security

Only fields required for the task are processed from backup jobs, error logs and retention policies. Source-system permissions are preserved, and unnecessary personal, technical and security-sensitive data is minimised before being sent to the model. Every retrieval, recommendation, human change and target-system action is written to the audit log.

Who this suits

Frequently asked questions