The context layer
your AI agents
can actually trust.
Your AI queries data but doesn't understand it. Dawiso connects your catalog, business glossary, and lineage into one governed context, reachable by any AI agent through MCP.
- Claude, Copilot, Cursor: one MCP connection
- AI drafts the context, your stewards approve
- SOC 2 Type II · ISO 27001 · GDPR
Every source feeds one context.
Databases, warehouses, BI tools, and pipelines flow into a single governed context your AI can query. We add new connectors every month.
Trusted by data teams at leading enterprises
This is what your AI gets to work with
Real product screens: AI-generated context, the MCP connection, and the relationships your agents reason over.
From scattered metadata
to context your AI can trust.
Three outcomes teams notice in the first month with Dawiso.
We have a clear overview of data flows. Before Dawiso, it was complicated to see where data comes from and have all sources documented in one place. Dawiso made this easy with comprehensive data lineage. Support is always there for us when needed.
Utilizing strong expertise in initial discussions and building robust partnerships during implementation led to exceptional results, enabling the project to go live in a very short timeframe.
The finest thing about Dawiso is how it makes compliance easier for expanding companies. It provides governance that adjusts to your requirements, making it simple to stay up to date on the rules without becoming overwhelmed by their complexity.
What happens in the demo
A live 30-minute session against your stack. Here is the full agenda.
Tell us your messiest dataset
You describe the data problem you want solved: broken lineage, vague glossary, missing ownership, AI context. We tailor the demo to it.
Watch your AI get context
We connect a representative source, scan it, and show an AI agent answering from your governed context through MCP, on data that looks like yours.
Get an honest "fit / no fit"
You get a direct answer on pricing and implementation timeline. If Dawiso is the wrong tool for your situation, we say so on the call and point you to a better one.
Quick answers
The questions data leads ask us before booking. The rest, we cover live.
What is a context layer for AI in simple terms?
A context layer gives AI agents the business meaning behind your data: definitions, relationships, ownership, and lineage. Instead of seeing raw columns, the AI understands what "revenue" means in your business and answers accordingly.
What is the difference between a context layer and a semantic layer?
A semantic layer translates technical data into business language for reporting. A context layer goes further: it adds lineage, governance, and process context that AI agents need for trustworthy answers, and exposes it through MCP so any agent can query it.
How does a semantic layer work with AI?
It gives AI consistent definitions and metrics. When an agent queries data, it uses the layer to understand what "customer" or "revenue" means in your business, which prevents misinterpretation. Dawiso connects that layer to any LLM through the Model Context Protocol.
What is MCP (Model Context Protocol)?
MCP is an open standard from Anthropic that connects AI agents and LLMs to external tools and data. Dawiso runs a production MCP Server, published in the Databricks MCP Marketplace, with both read and write access. Your AI reaches governed context, glossary, and lineage in real time, tested with Claude, Cursor, and Copilot.
What does it cost?
Pricing is per active user plus a flat platform fee, typically a fraction of what Collibra or Alation quote for comparable scope. We quote your exact number on the call once we know your source count.
Is the demo a sales pitch?
The demo is a working session on your data and your stack. You tell us where AI is guessing today, we run the context layer live in Dawiso, and you leave with a clear "fit / no fit" call.
Book your 30-minute working session
Bring your data, your stack, and your questions. We run the demo live in 30 minutes.