




%20Integration%C2%A0.png)

A context layer provides AI agents with business definitions, data relationships, and documentation, enabling them to understand what your data means, not just what it contains.
A semantic layer translates technical data into business language. A context layer goes further. Adding data lineage, governance, and business process context that AI agents need for trustworthy answers.
A semantic layer gives AI consistent business definitions and metrics. When AI agents query data, they use the semantic layer to understand what "revenue" or "customer" means in your business, preventing misinterpretation.
A data catalog for AI goes beyond traditional data discovery. It provides business context, lineage, and governance metadata that AI agents need to understand and use your data correctly. Use Dawiso MCP to connect your catalog to the AI models.
AI agents query data catalogs to understand what datasets exist, what they mean, how they're related, and who can access them, making AI responses contextually accurate and compliant.
MCP is an open standard that connects AI agents and LLMs with external tools, data, and business context. Dawiso provides its own MCP Server, allowing your AI to access and reason with your enterprise data and metadata. You can read more about it in this article.