VISEON Catalog for Qlik · vCat for Qlik
Your AI should understand what you mean before Qlik computes the answer.
VISEON Catalog for Qlik brings governed business meaning into your Qlik Cloud Analytics tenant. A Qlik extension drafts a description for every master measure, dimension and field in your apps; your data steward approves each one; the approved definitions are written back to your apps and served to AI agents over MCP. Qlik Answers and the Qlik MCP Server then work from your meaning, not the model’s guesswork.
Why Qlik needs it
Qlik computes the answer. Something has to settle the meaning first.
The Qlik MCP Server is good at running the calculation. It isn’t built to decide what your business terms mean, or which of several master measures answers the question. VISEON Catalog holds that governed meaning for every platform in your estate; this page shows how it works inside Qlik.
How it works in Qlik
From your master items to governed concepts
vCat runs at the edge, close to your tenant, in two parts working together: a Qlik extension, which scans your Qlik Cloud Analytics estate and drafts a description for the master measures, dimensions and fields already in your apps; and a portal, where your data steward reviews each draft. Nothing is written back to your apps, or served to AI agents over MCP, until a human has signed it off.
- Step 1Your Qlik appsThe master measures, dimensions and fields already built into your apps.
- Step 2vCat extensionScans the apps and drafts descriptions, metrics and relationships.
- Step 3Candidate mappingDrafts become candidate business concepts: proposals, not facts.
- Step 4 · HumanSteward reviewYour data steward approves each one in the vCat portal. vCat proposes; your steward approves.
- Step 5Governed master itemsThe approved definition, written back to your master items.
That matters because Qlik Answers already prefers master item descriptions over its own inference, when they exist. The gap in most tenants isn’t Qlik’s logic; it’s the descriptions themselves. Writing a clear, correct description for every master measure and dimension by hand doesn’t scale. vCat closes that gap with an automated, human-approved way to keep them complete.
In our own testing
Before governed descriptions were in place, Qlik Answers’ Thinking mode would occasionally fall back on the model’s training data rather than the app’s data. After they were written back into the app, it stayed inside the app’s data. It’s the before and after we can show you on your own tenant.
Alongside Qlik
Where vCat sits alongside Qlik’s catalog, Qlik Answers and the Qlik MCP Server
vCat isn’t a replacement for Qlik’s own tools. It’s the layer that makes them work better.
Qlik Answers & Qlik’s catalog
Qlik’s catalog and Qlik Answers use your master item descriptions and data products where they exist, and fall back on general LLM reasoning where they are missing. vCat keeps those descriptions complete, approved and continuously governed, so the fallback is rarely needed.
The Qlik MCP Server
The execution layer: it gives an AI agent governed access to your apps, data products and datasets, runs the Qlik engine and returns a computed answer. vCat MCP sits ahead of it in the same request, resolving intent, meaning and the right master measure before Qlik computes anything.
VISEON Data Assurance
vCat tells your AI which number you mean. VISEON Data Assurance tells you whether that number can be trusted, scoring every row of the app data and QVD files behind it.
vCat is built by VISEON, not a Qlik product. Qlik, Qlik Answers and Qlik Cloud are trademarks of QlikTech International AB.
See it on your data
See vCat on your own Qlik tenant
We’ll show you the before and after on your own Qlik Cloud Analytics estate. VISEON Catalog for Qlik is from £12,000 per annum.