Turn manufacturing spend data into negotiation power.
Manufacturers buy the same materials from many suppliers across many plants, yet price variance hides inside catch-all material groups. Mithra builds a validated taxonomy and surfaces the average, highest, and lowest price for every material.
A tool that gives you everything but visibility.
Many manufacturers run an internal tool that can't surface what the group is buying. Catch-all material groups like "Material Others" lump categories together, buyers can't trust the classifications, and there's no basis to spot negotiation opportunities. Defining a taxonomy by hand stretches into months.
Catch-all material groups
"Material Others" hides multiple categories buyers can't read.
Unreliable classifications
Material codes buyers can't trust to drive decisions.
No negotiation basis
No way to compare prices for the same material across plants.
Manual taxonomy, slow
Hand-built category trees are error-prone and take months.
AI suggests, your team validates.
Mithra pairs its intelligence with your domain expertise in a tight loop, proposing classifications your buyers validate, then keeps the taxonomy alive as products evolve.
- A validated baseline taxonomyAI proposes the structure; your team refines it in weeks.
- Reclassify all spendEvery transaction, including "Material Others", classified with high accuracy.
- Average, highest & lowest priceThe same material across suppliers and plants, side by side.
- Govern over timeNew products and acquisitions absorbed without losing integrity.
Spend data as a strategic asset.
"Material Others", solved
The catch-all bucket becomes a clean, granular taxonomy.
Negotiation, aimed
Price per material across suppliers backs every negotiation with data.
Future-proofed
The taxonomy maintains itself as products launch and acquisitions land.
Decisions on data
Category strategy runs on evidence, not intuition.
Franke turned messy spend data into strategic advantage, in weeks.
Whole swaths of spend were buried in a catch-all "Material Others" category. In about three weeks, Mithra and Franke built a validated, AI-assisted taxonomy and reclassified the data.
"We went from fragmented visibility and misclassified spend to a robust, AI-assisted taxonomy and classification in just weeks."
Angela RametsiChief Procurement Officer, Franke Management
Ready to transform your procurement data?
We'll show you what Mithra finds in your own spend, from a validated taxonomy to negotiation-ready price comparisons, in weeks.