Certified semantic layer
One definition per metric, owned by your team, applied to every answer.
Why QuaerisAI
Because “the AI said so” isn't good enough for a number in a board meeting.
QuaerisAI agents answer from certified definitions your team already owns, not a model's best guess, and every answer carries a citation back to its source.
Governed answer
What was our Q3 enterprise churn rate?
4.2%Enterprise churn, Q3
revenue.subscriptions_certified · definition v14
Access checkedLogged to audit trail
0Governed deployments
0Lift in data interaction
0Reduction in engagement hours
0BI cost reduction
The core difference
Certified, not improvised.
When most AI analytics tools don't know an answer, they generate one anyway. QuaerisAI doesn't.
An ungoverned model
Improvises a metric definition on the spot
Same question, asked twice, can return two different numbers
No record of which table or logic produced the answer
Access filtered after the query runs, if at all
QuaerisAI
Resolves against a certified, versioned definition
The same question returns the same answer, every time
Every answer cites its source table and definition version
Access enforced at query time, before the query runs
How it's built
Four things that don't change, no matter how the model market moves.
Query-time access
Permissions checked before a query runs, not filtered after the fact.
Warehouse-native
Runs against Snowflake, BigQuery, Databricks, and more, in place. Zero rows copied.
Bring your own model
Switch the underlying model without rebuilding governance or definitions.