Trustworthy analytics, and the agent that builds it.
One platform with two ideas: anyone can ask their data a question and get a correct, governable answer, and an agent works alongside your analysts to define the metrics and maintain the data engineering behind it.
Self-serve analytics you can trust
You ask in plain English. The model's only job is to align on exactly what you mean and translate it into the language of your data, it never writes the SQL. A deterministic engine does that, the same way every time.
So the answer is correct and governable, and every question and its answer is logged with full lineage. No hallucinated queries, nothing to take on faith.
Ask your data →An agent that works with your analysts
Requests arrive as tickets, emails, half-defined asks. The Agentic Analyst reads them across your tools, then works with your analyst to pin down the exact math, the analyst owns the definition, the agent does the engineering.
It codifies that definition into the governed catalog and answers the request. The data engineering gets done, and the team's knowledge is captured instead of walking out the door.
See the Workspace →One governed catalog underneath both
Both ideas run on the same foundation: a curated semantic catalog of business metrics, each with one pinned definition. The Workspace is how analysts build and maintain that catalog; Ask is how the business consumes it. Every answer from either side is role-checked, scanned, capped, and recorded with verifiable provenance, which is what makes it usable in a regulated enterprise.
See the live data health →