Context modeling for AI analytics at scale
Omni’s suite of tools turns institutional knowledge into code-based semantics for data agents.
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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
Build your semantic layer with context that compounds
Start querying with agents in minutes. Refine context as your business evolves.
Let AI write the YAML for you
Ask Omni’s Modeling Agent to create views, define joins, or optimize Topics for AI. It returns YAML you can review and commit.
Create governed datasets AI can't get wrong
Set up Topics: structured datasets that tell agents which tables join, how to make sense of similar metrics, and what questions each dataset answers.
Train your agent in-line
Agent gets something wrong? Tell it in your next message, and it’ll draft a fix for your review.
Endorse queries for agents to replicate
Designate canonical queries so agents learn the shape of a good answer. A handful of well-chosen examples covers dozens of variations.
See what your users ask
Admins can see row-by-row details about their team’s AI usage. Find queries worth endorsing or context gaps to improve.
Maintain a single source of truth
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.
Omni’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
