Why is Minerva not just another LLM?

The AI tool market is growing at breakneck speed. Every month brings a new language model promising to revolutionise work. In all this noise, it is easy to dismiss Minerva as just another LLM. But that is a fundamental misunderstanding — Minerva was designed from the ground up with one specific task in mind.

The problem with general-purpose language models

Classic LLMs — ChatGPT, Claude, or Gemini — are general-purpose models. They can write poetry, translate languages, and answer questions from nearly every domain. But when it comes to analysing complex tender documentation, their versatility becomes a weakness. They do not understand the legal context of public procurement, cannot reliably verify compliance with criteria, and — most critically — they hallucinate.

In procurement, hallucination is not a minor inconvenience. It is the risk of submitting a non-compliant bid, missing a critical exclusion criterion, or miscalculating. The consequences can mean losing your bid bond, being excluded from the procedure, or — worst case — accepting a contract on terms the company cannot fulfil.

Evidence-based architecture

Minerva does not generate answers from statistical memory. Every analysis is grounded in the actual document — the system points to the exact passages that support its conclusions. Users can verify the source of every piece of information with a single click. This approach is radically different from conventional chatbots.

Furthermore, Minerva is specialised in the legal and technical language of public procurement. It understands tender specification structures, identifies evaluation criteria, catches non-standard contract clauses, and compares requirements against the bidder's profile. It is not a general assistant — it is a tool built by procurement practitioners, for procurement practitioners.