Data agents you can trust.
We forward-deploy with data teams to make the data agents you already use trustworthy, secure, and access-aware. The difference between hoping your agent's answers are right and knowing they are.
Bring your own agent.
Use whichever data agent you already have — there are plenty of good ones. We don't sell you another agent. We make the one you've chosen trustworthy enough to put in front of an executive.
Claude 
Snowflake 
+ others Which column is canonical. What "active user" means here. Which of the three definitions of "churn" is the real one. An agent inherits every undocumented assumption in your warehouse and states it back with total confidence. Getting it right — and keeping it right — takes living evals, the right context, and semantic models that improve the agent over time. That work is bespoke at every company, and it's the whole job.
Eval Builder
Every frontier model ships with an eval suite. Almost no enterprise has one for its own agents — and building them by hand is punishing. But you already own the answer key: your most-used dashboards and ETL jobs were built to produce numbers the business trusts. We turn them into a custom eval suite tailored to how your organization actually asks questions.
Eval Scorer
We connect your agent to the eval and grade every answer — SQL match and value match — tracking performance over time. Where it falls short, we show actual vs. expected and exactly what to change to score higher. And every time your context or semantic layer changes, we re-run the suite, so quality never silently regresses.
Context Resolver
Context from different corners of the org often disagrees — two tables that each claim to be the source of revenue, an "active user" that means one thing to Marketing and another to Finance. We surface these conflicts and give you a workflow to resolve them, so your agent answers from a single, agreed source of truth.
Semantic Model Builder
Reliable answers still require a semantic model: a structured definition of what your data actually means. Hand-building one is slow. Our agentic builder generates and maintains the layer that powers trustworthy answers — based on your ETL code, organizational context, data profiles and, most importantly, your query logs.
Migration Swarm
Moving across data warehouses, BI, or ETL tools? A fleet of purpose-built migration and validation agents moves you in a fraction of the time — and rebuilds the semantic foundation correctly on the way in.
Mark has worked on separating data wheat from chaff for over a decade. First for humans, now for agents. He was previously the co-founder/CEO of Stemma, the modern data catalog used by SoFi, iRobot and many others, and created Amundsen, the first modern open-source data catalog.
LinkedIn ↗
Mark created Amundsen — the first modern open-source data catalog — at Lyft, to make data discoverable and trustworthy.
He went on to found Stemma, the Sequoia-backed data catalog — later acquired by Teradata.
Find out whether your agent is telling the truth.
If your data agent is getting answers wrong — or you want it right before it ever reaches an executive — let's talk.