Dawiso

Dawiso

Metadata Context Platform for Trustworthy AI

50 followers

Dawiso is an AI-powered data catalog that helps teams discover, understand, trust their data, and now fuels trustworthy enterprise AI with its new AI Context Layer. It automatically builds the business context that AI systems need. Its context layer connects directly to AI agents via (MCP) so they can access governed knowledge. Dawiso includes interactive data lineage, a business glossary, and unstructured data governance in one governed source of truth.
This is the 2nd launch from Dawiso. View more

Dawiso AI Context Layer

Launching today
Connect AI agents to governed metadata via MCP
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.
Interactive
Dawiso AI Context Layer gallery image
Dawiso AI Context Layer gallery image
Dawiso AI Context Layer gallery image
Dawiso AI Context Layer gallery image
Dawiso AI Context Layer gallery image
Free Options
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What do you think? …

Lenka Zemanová
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?
Zeiki Yu

Congrats on the launch — love how Dawiso brings trusted context to enterprise AI.

shreya chaurasia

The framing around context being the missing layer resonates. We’ve seen LLMs give confident but wrong answers when metadata is thin or inconsistent.

Curious how much of the context generation is automatic versus refined manually by domain experts.