🤖 How can an AI agent be made truly reliable in a business context?

In this article, our consultant Brahim KERDAD presents an original architecture: Gold/Silver Retrieval, designed to reduce hallucinations and improve the robustness of LLM-based agents.

In particular, we discover how this approach makes it possible to:

• clearly distinguish between reasoning data (Gold) and response data (Silver),
• structure the core business in the form of a knowledge graph (GraphRAG),
• avoid contradictions associated with overly loaded traditional RAGs,
• intelligently orchestrate processing according to the type of question,
• and guarantee more consistent, explainable and reproducible responses.

The result: AI agents capable of reasoning in a controlled manner while effectively exploiting business knowledge.

👉 A concrete approach to move from impressive chatbots to truly reliable AI agents.

 

Designing a reliable business AI agent GoldSilver Retrieval architecture