The missing layer between your data stack and AI
Kaelio auto-builds a governed context layer from your warehouse, BI tools, and semantic definitions so AI agents answer with your business logic, not their own.
Auto-built from what you already have
Schema, metrics, dashboard logic, lineage, and domain knowledge. Pulled from your existing tools, not maintained in a new one.
Works with your semantic layer, not against it
Kaelio extends your dbt, Looker, or Cube definitions with the context they're missing: dashboard intent, business rules, and tribal knowledge.
One governed source for all AI agents
Whether it's Kaelio's data agent or your own internal tools, every agent answers from the same trusted foundation.
Trusted by data teams at
What the context layer pulls together
Schema
Tables, entities, valid joins
Metrics
dbt, Looker, Cube definitions
Lineage
Source-to-dashboard mapping
Domain rules
Business logic and exceptions
Works with your existing stack
Plus 900+ more connectors
Enterprise ready
Up and running in 30 minutes
From connected stack to governed context layer
Connect your stack
Kaelio ingests schema, lineage, and metric definitions from your warehouse, dbt, BI tools, and docs.
Review the context layer
Your data team reviews auto-generated definitions, resolves conflicts, and adds domain knowledge.
Expose to agents
Kaelio's data agent or your own tools query the governed layer. Every answer is grounded and source-cited.
The problem it solves
Why semantic layers alone aren't enough
Metrics defined in five places, governed in none
dbt says one thing, Tableau says another, the spreadsheet says a third. Fixing it manually is a 6-month governance project.
Agents hallucinate without structured context
Without a governed layer, every AI tool builds its own understanding. Same question, different answer every time.
Dashboard logic never makes it into the semantic layer
Filters, calculated fields, visualization logic. It all lives in Tableau or Looker, invisible to your metrics layer.
Domain knowledge lives in people's heads
Business rules, exceptions, naming conventions. No semantic layer captures tribal knowledge. Kaelio does.
Works with every agent
One context layer, any AI interface
The context layer is consumed by Kaelio's own data agent, but it also powers any external agent your team builds or adopts.
Kaelio Data Agent
Built-in agent for ad hoc questions, digests, and dashboards
Custom agents
Your own internal agents via Kaelio's API and MCP server
Claude (Cowork & Code)
Give Claude governed data context for analysis and code
ChatGPT
Ground ChatGPT answers in your actual business definitions
Cursor / Windsurf
Let coding agents query live, governed metrics while building
Any MCP-compatible tool
Any agent that speaks MCP can query the context layer directly
See how it works with your stack
Bring your warehouse, BI, and semantic layer questions. We'll walk through how Kaelio ingests what you already have and turns it into a reliable foundation for AI analytics.