Define the intended suggestion
Name the decision aid, covered population, permitted output and consequence if a proposal is wrong.
Workflow blueprint
Evaluate an accounting suggestion before accepting an AI label
A challenge register for buyers testing machine-proposed categories, matches, explanations or entries.
Provide an evidence-led evaluation method without claiming Codeblix AI, continuous learning, accuracy, fraud detection, automatic posting or replacement of professional judgement.
TL;DR — Provide an evidence-led evaluation method without claiming Codeblix AI, continuous learning, accuracy, fraud detection, automatic posting or replacement of professional judgement.
Attach output to its input snapshot
Preserve source documents, disclosed version, supplied explanation and unresolved uncertainty.
Run challenge cases
Test missing sources, changed suppliers, duplicates, ambiguous examples and late corrections.
Keep acceptance reversible
Record the reviewer decision, alternative considered, correction trigger, superseded output and reversal evidence.
Page-specific decision aid
A suggestion-lineage, reviewer-challenge, correction and reversal register
The register freezes a supplier document set, stores one proposed category and explanation, records the disclosed model or rule version, flags absent evidence, presents an alternative, captures the reviewer challenge, accepts or rejects the output, then preserves a correction trigger and tested reversal.
- ✓A fluent explanation is not transaction evidence.
- ✓Confidence does not grant posting authority.
- ✓Human acceptance must remain traceable and reversible.
Scope first
What Codeblix would confirm before implementation
This page is an operational blueprint. The final workflow, screens, permissions and integrations depend on your current process and agreed implementation scope.
- ✓Machine text never becomes supporting evidence by repetition
- ✓Every accepted proposal names a responsible reviewer
- ✓Rejected suggestions remain available for evaluation
- ✓Model accuracy fraud detection automatic posting and AI feature claims excluded
Relevant Codeblix foundations
Review the existing product areas that support the proposed workflow.
Use the related planning tools
Run the operational calculation, save the result in the URL and share it with your team.
Map this workflow to your operation
Tell Codeblix how work moves today. We will confirm the practical scope before proposing an implementation.
Discuss your workflow