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Documentation Index

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Before anyone on your team can ask questions in ClarityQ, the Context Layer needs to be built. The Context Layer is what teaches ClarityQ how your business thinks about its data — it bridges the gap between raw database tables and the business concepts your team uses every day.
The Context Layer is a prerequisite for using Ask Anything. The more complete and accurate your context, the better ClarityQ’s answers will be.

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What’s in the Context Layer?

The Context Layer is made up of five components:

Table Catalog

A live inventory of the tables and columns in your data warehouse. ClarityQ automatically discovers and indexes your schema.

Event Catalog

A catalog of product events, parameters, and user properties — synced from your analytics tracking and mapped to the semantic catalog.

Semantic Catalog

The core business logic layer. Define metrics, features, segments, and dimensions that reflect how your organization measures and analyzes data.

Memory

Persistent context that ClarityQ retains across conversations — at the personal and product level.

Skills

Reusable analysis methodologies that guide the AI agent through complex, multi-step workflows consistently.
The components build on each other. Follow this order for the best results:
1

Table Catalog

This happens automatically after you connect your data warehouse. ClarityQ discovers your tables, columns, and schema structure. Review the results, act on discovery findings, and build entities from your tables.
2

Event Catalog

If your product tracks events (e.g., via Mixpanel, Amplitude, or custom tracking), set up the Event Catalog. Use the Missing Description Wizard to fill in gaps, then sync events to the Semantic Catalog.
3

Semantic Catalog

This is where you define business logic. Create dimensions, metrics, features, and segments that map to how your team actually talks about data. ClarityQ’s AI agent actively helps build these components — leveraging your existing definitions, documentation, and data structure.
4

Memory

Add the knowledge that doesn’t live in your database — business rules, naming conventions, domain-specific context. Memory improves answer quality over time.
5

Skills

Once your team has established repeatable analysis patterns, encode them as skills. The agent will follow these step by step for consistent, high-quality results.
You don’t need to complete every component before using Ask Anything. Once your Table Catalog and a few core Semantic Catalog components are in place, you can start asking questions — and continue building context as you go.