We built Mithra to fix procurement's data foundation.
Every ambitious procurement team hits the same wall: spend data too fragmented to trust, let alone run AI on. Mithra fixes it at the source, one governed foundation, built once and kept clean.
The problem we kept seeing in procurement organizations
Mithra was founded by a team that had spent years working with enterprise procurement organizations and kept running into the same wall: brilliant procurement leaders with ambitious transformation programs, blocked at every turn by data that wasn't trustworthy enough to build on.
The dashboards existed. The ERP systems had the data. But the taxonomy wasn't consistent. The supplier list was a mess. The category codes hadn't been reviewed in five years. Every analytics project started with weeks of data cleanup before any real analysis could happen.
We built Mithra because that problem deserved a purpose-built solution. Not a general-purpose data cleaning tool. Not another layer of dashboards over dirty data. A procurement-native platform that understands spend classification, supplier normalization, taxonomy governance, and opportunity analysis at the depth enterprise organizations require.
The name Mithra comes from the ancient deity of contracts and the rising sun, an entity associated with truth, keeping promises, and illuminating what was previously in the dark. That felt right.
Clean data for agentic procurement.
Mithra's mission is to give every enterprise procurement organization a trusted data foundation, clean, classified, governed, and ready for AI agents, analytics, and savings execution. We believe procurement should not have to fight its own data to do its job.
Procurement agents are only as good as the data they reason over.
The industry is embracing AI agents, autonomous sourcing, and intelligent automation. These capabilities are genuinely powerful but they're fundamentally dependent on clean, governed, semantically consistent data to produce trustworthy outputs.
See the productSame question. Same agent. Two answers.
It's the same AI assistant both times, and it asked the same question. The only difference is the data beneath it, raw on the left, prepared by Mithra on the right.
Trusted agents require trusted data.
Highly optimised, benchmarked taxonomy
Mutually exclusive categories, benchmarked against industry, so every transaction has exactly one home.
Correctly classified spend
Totals reflect every relevant transaction, not just the obvious ones.
Normalized supplier identities
One vendor, one complete relationship across every alias and entity.
Harmonized material specifications
Equivalent items compared across the enterprise, in any language or format.
Mithra keeps the taxonomy, suppliers, and materials beneath your agents clean — so the answers stay right.
Recognized for procurement data innovation
Spend Matters Future 5
Google Cloud Partner
25 Hottest European Procurement Startups
Built by people who understand procurement data deeply
Mithra is built by a team with deep roots in enterprise procurement, data engineering, and applied AI across Amsterdam and Eindhoven.
Rasa Raoufi
Backed by the people who built modern procurement.
Every procurement team runs into the same wall, the data underneath it isn't clean. Mithra is solving that foundational problem, and that's what makes everything above it work.
Noah EisnerFounder of CoupaProcurement has spent a decade buying analytics and AI on top of data nobody trusts. Mithra fixes the layer everyone else skipped.
Dr. Marcell VollmerEx VP, SAP & CelonisI've spent my career in spend analytics, the hardest part was never the dashboard, it was the data. Mithra has built exactly the foundation this market has been missing.
Fabrice SaporitoEx CEO, SievoThe move to agentic procurement only works if the data underneath is governed and reliable. Mithra is building that backbone the right way.
Moritz ZimmermannEx CTO, SAP & Founder of HybrisBased in the Netherlands
Want to see what Mithra can do with your procurement data?
Our team understands procurement data challenges because we built a product specifically to solve them. Let's talk about yours.