AI fails in enterprises not because of models, but because it lacks context. Dawiso’s AI Context Layer turns data catalogs into the semantic backbone for AI. Defining meaning, ownership, access, and relationships. Connected to AI agents via MCP, it enables AI to answer the right question, for the right user, with the right data. This context is generated automatically through metadata scanning and AI enrichment, with human-in-the-loop governance ensuring it stays relevant, and trustworthy.
Hello!
We kept seeing teams add chatbots and LLMs on top of their data, only to get inconsistent or misleading answers. The missing piece is context - the kind data catalogs already provide.
With Dawiso’s AI Context Layer, we focus on giving AI real business context, generated automatically after metadata scanning and governed with humans in the loop. This context is then shared with AI agents via MCP, so AI can answer the right question for the right user.
We would love your feedback! How are you making sure AI actually understands your data today?
