Own the standard for procurement data quality.
You set the rules for taxonomy and supplier governance. Mithra enforces them everywhere, measurable and fully auditable.
Why: Analyzing supplier name and spend pattern against your taxonomy.Why: Matched on supplier profile and line description; logged with reason code for audit.
Why: Supplier name matches two taxonomy branches; comparing spend patterns.Why: Spend pattern favors Contract Manufacturing; logged with reason code for audit.
Why: High-confidence auto-classification, logged with reason code for your permanent audit trail.
Setting the standard is easy. Enforcing it is the hard part.
The CoE defines the taxonomy and data-quality rules, but enforcement depends on hundreds of people classifying data consistently every day. Without a machine in the loop, the standard erodes and you can't prove quality at audit.
Standards that erode
A taxonomy that's ignored the moment data lands inconsistently.
Manual enforcement
Quality depends on people remembering the rules.
No quality metric
No single, trusted number for classification accuracy.
Audit exposure
No defensible trail of who decided what, and why.
Your standard, machine-enforced and auditable.
Mithra encodes your taxonomy and governance rules, classifies new data against them, and routes only the exceptions to a queue your team controls. Every decision is logged with a confidence score and reason code.
- Taxonomy ownershipThe CoE owns the structure; Mithra enforces it everywhere.
- Exception-based reviewOnly low-confidence decisions reach a human queue.
- Quality as a numberClassification accuracy and coverage tracked continuously.
- Full audit trailEvery decision and override logged and reversible.
Govern by exception, prove quality on demand.
Enforced standard
Your taxonomy applied automatically to every new transaction.
Measured quality
A single, trusted accuracy and coverage number to govern by.
Less manual work
Teams review exceptions, not every line.
Audit-ready
A complete, reversible trail for every decision.
Make your data standard enforceable.
Share a sample extract and we'll show you classification against your taxonomy, the exception queue, and the quality metrics behind it.