Conversational agents are becoming the front door to enterprise data. Business users ask questions in plain language and expect a trustworthy answer, without writing SQL or waiting on a report.
The demand is real and accelerating. The question is no longer whether you'll build agents; it's whether you can trust the ones you ship.
An agent is only as trustworthy as the process behind it. So manage the entire lifecycle as code (the data model, the agent, its tests, and its schedule) natively on Snowflake, with dbt.
Same discipline you already apply to the rest of your data platform: version it, review it, test it, promote it.
Every change is in Git, diffed, and approved in a pull request before it reaches users.
Evaluations score the agent against known answers; ship only when it clears the bar.
The same code targets dev, staging, and prod. No rebuilding by hand per environment.
Deliver the same governed agent to Snowflake Intelligence, Teams, an API, or MCP.
Before an agent ships, it's scored against a set of known questions and answers. The bar to promote: at least 95% answer correctness. Fall short, fix the right layer, and re-run.
Accuracy stops being a gut feeling and becomes a metric you can track, compare across versions, and hold the line on.
The same code promotes from a developer's sandbox to production: no hand-rebuilding, no drift. Automated pipelines build and test on every change; scheduled jobs keep it fresh.
Each engineer builds in their own space, so nobody overwrites anyone else.
Changes merge through pull requests; CI builds and tests before prod.
Scheduled rebuilds and evaluations run automatically, with no manual toil.
Ask-your-data experience
In the flow of work
Embed in your apps
Open agent interop
One governed agent, delivered to every surface your users already live in.
Ready to go deeper with your team? The full technical walkthrough lives alongside this deck. Open the technical walkthrough.