There’s relevant, untapped business context everywhere. Omni stands out because it makes all of our knowledge structured and durable for smarter AI. It gets more valuable as more people and more AI tools depend on it. Building in Omni’s governed context graph lets us capture institutional knowledge that compounds.
Sarah Fischbach, Staff Analytics Engineer
Start querying with agents in minutes. Refine context as your business evolves.
Ask Omni’s Modeling Agent to create views, define joins, or optimize Topics for AI. It returns YAML you can review and commit.
Set up Topics: structured datasets that tell agents which tables join, how to make sense of similar metrics, and what questions each dataset answers.
Agent gets something wrong? Tell it in your next message, and it’ll draft a fix for your review.
Designate canonical queries so agents learn the shape of a good answer. A handful of well-chosen examples covers dozens of variations.
AI Hub gives your team one place to observe how AI is performing, improve what needs fixing, and validate that it's working.
Metadata from Snowflake, Databricks, and dbt automatically gets used by Omni’s agents. Logic stored in Omni can be pushed upstream. Keep context consistent across systems.
Read case studyOmni’s AI isn’t a black box. We’re able to learn from our own usage and take action. We still have control — and that’s crucial to ensure AI is trustworthy for users across our organization.
Priya Gupta, Head of Data
