{"id":11574,"date":"2026-01-22T11:45:52","date_gmt":"2026-01-22T10:45:52","guid":{"rendered":"https:\/\/www.retarus.com\/blog\/en\/warum-wir-mistral-als-fundament-fuer-retarus-idp-gewaehlt-haben\/"},"modified":"2026-01-30T14:15:58","modified_gmt":"2026-01-30T13:15:58","slug":"why-we-chose-mistral-as-the-foundation-for-retarus-idp","status":"publish","type":"post","link":"https:\/\/www.retarus.com\/blog\/en\/why-we-chose-mistral-as-the-foundation-for-retarus-idp\/","title":{"rendered":"Why We Chose Mistral as the Foundation for Retarus IDP"},"content":{"rendered":"\n

Artificial intelligence is fundamentally changing how organizations process documents. In Intelligent Document Processing (IDP), powerful language models make the difference between \u201ca bit of automation\u201d and truly scalable end-to-end workflows \u2013 higher automation rates, better data quality, and faster cycle times.<\/p>\n\n\n\n

But the more capable AI becomes, the more critical the question is: Where does the data go \u2013 and who stays in control? This is exactly where we take a clear stance. Our IDP solution<\/a> is architected around Mistral<\/a> \u2013 a leading European AI model that combines performance with data sovereignty.<\/p>\n\n\n\n

Why AI Alone Isn\u2019t Enough \u2013 and Why Architecture Matters<\/strong><\/h2>\n\n\n\n

Many IDP solutions \u201cuse AI\u201d yet still fail when faced with real-world documents: varying formats, inconsistent structures, domain-specific nuances, complex line items, and context dependencies. The reason is simple: performance alone is not enough. What matters is whether a model can understand semantic complexity \u2013 instead of merely matching patterns.<\/p>\n\n\n\n

This is where \u201cMistral Small 24B<\/a>\u201d comes in: a European large language model with 24 billion parameters, purpose-built for:<\/p>\n\n\n\n