Advanced Document Search (RAG)
Connect your AI models to your internal data to free your teams from tedious searches and make decision-making more reliable.
The Challenge
Your staff spend up to 30% of their time searching for critical information in your procedures, contracts, or knowledge bases. A generic LLM would invent false answers (hallucinations), creating a major risk for decision-making.
The Technological and Human Approach
We design custom RAG (Retrieval-Augmented Generation) architectures. Using semantic 'chunking' and hybrid 'cross-encoder' re-ranking, the AI retrieves the exact information and systematically cites its source. Your teams put the available information directly to work to create value.
Architecture and Sovereignty
We version our indexing and actively monitor performance, with safeguards against prompt-injection attempts. We deploy securely via cloud APIs (Zero Data Retention) or by hosting local models (Mistral, Llama) on your own infrastructure to guarantee total sovereignty over your data.
Tech stack
