How Genie Ontology powers product development at Databricks

Genie Ontology addresses a core challenge for enterprise AI: the lack of institutional knowledge required to interpret business data correctly. Unlike general-purpose agents that rely on web searches or code generation, Genie Ontology provides AI with continuously updated definitions, rules, and trusted sources specific to an organization. This context is drawn from certified assets in Unity Catalog and learned knowledge from dashboards, documents, and applications across the enterprise.

The Databricks product team uses Genie One to automate weekly adoption reviews, replacing manual data gathering and analysis. Product managers begin by asking Genie to generate a standardized report that identifies adoption hotspots across multiple platforms, including web, mobile, and collaboration tools like Slack and Teams. Genie combines certified metrics, governed KPIs, and live documents to produce an executive-ready review without requiring repeated queries or token-intensive exploration.

Genie Ontology ranks sources by authority using OntoRank, prioritizing human-curated and certified assets before exploring learned snippets. This ensures responses are grounded in the most reliable data, such as certified weekly active users metrics or governed KPIs defined company-wide. The system also supports forecasting directly within Genie One, allowing product managers to analyze trends and flag accounts for review without waiting for data science teams.

The practical impact is demonstrated through a real use case where a product manager schedules recurring adoption reviews, investigates unexpected user spikes, and creates a shareable agent for ongoing queries. By leveraging Genie Ontology, the team automates workflows, enforces governance, and enables non-technical users to access trusted business insights without manual intervention.