Assemble, test, and ship the business context every AI agent needs to produce accurate, trustworthy answers.
Context Engineering Studio
Context Engineering Studio is where you build context repositories. A context repository is the canonical definition of what your data means, scoped to one use case: a portable semantic layer (the metrics, dimensions, relationships, and rules that define your data) that references the Atlan assets it's built from and publishes to each engine in the format that engine expects.
- Deterministic and governed. Every linked asset points back to its governed source rather than being copied, so the same context produces the same repository and stays governed at its source.
- Tested before it ships. Run a generated question set against the repository and read the per-question failures before business users see them.
- One repository, many engines. Snowflake Cortex Analyst, Databricks Genie, dbt, and Claude each read the same model, generated on demand with a review step before you ship.
Deal-level pipeline snapshot, one row per opportunity per day.
Enable
Enable CES on your tenant, assign access to your team, and connect your query engine.
Assemble
Describe your use case, approve the assets CES proposes, refine the semantic model, and simulate with a question set to see where to improve.
Deploy
Review what each engine will receive, then deploy to Snowflake Cortex Analyst and Databricks Genie, render for dbt, and expose over MCP for Claude.