Review outputs
Check work against the standards that matter to the workflow.
- Defined quality and accuracy checks
- Review of uncertain or incomplete outputs
- Escalation to an agreed decision-maker
Operations
Support for AI
in everyday use.
Human review, exception handling, and ongoing improvements for deployed workflows.
Resolve exceptions
Handle the cases that need more than an automated next step.
- Failed-run triage and follow-up
- Incomplete records and ambiguous data
- Documented resolution and escalation paths
Improve performance
Use recurring issues to inform the next implementation change.
- Issue patterns and review findings
- Updates to prompts, workflows, and evaluations
- Documentation of changes and unresolved issues
An example review path
Every exception
needs an owner.
Define what the system can complete, what needs review, and who makes the final decision.
Illustrative workflowAI + human review
Flagged outputReviewResolve or escalate
Agree the review rules.
Specify the criteria that send an output to a person.
Record the decision.
Capture the resolution and route anything outside the agreed scope.
Feed findings into the build.
Use repeated issues to guide improvements.
Setting up support
Coverage built
around the workload.
Start with a workflow review. Agree the queue, review criteria, expected volume, service hours, access, and escalation path.
- What is reviewed and what is excluded
- Who resolves each type of exception
- How work and decisions are recorded
- When coverage is available and findings are reviewed
Work with FormalsNeed support
Need support
after deployment?
Tell us what is running and where human support is needed.
Discuss AI operations