DatabricksNicole EsibovProblem & solution
General-purpose AI agents fail on business questions because they lack enterprise context such as authoritative tables, business rules, and trusted experts; the missing institutional knowledge is scattered across dashboards, documents, and people. Databricks’ Genie Ontology addresses this by continuously updating institutional knowledge from certified Unity Catalog concepts and automatically learned snippets from dashboards, notebooks, SQL queries, and connected apps. OntoRank ranks sources by authority using certification, usage, and authorship signals, so Genie grounds answers in the most trusted and relevant data. In a weekly adoption review, a product manager prompts Genie, which uses MCP to search Google Docs and Jira while running live SQL for fresh analysis. The resulting report includes citations, forecasting, scheduling, and even conversion into a shareable Genie Agent, all within permission boundaries.
General-purpose AI agents lack the enterprise context needed to answer business questions correctly. Institutional knowledge about authoritative tables, business rules, and trusted experts is scattered across dashboards, documents, queries, and people, and it changes constantly.
Genie Ontology combines certified concepts from Unity Catalog with automatically learned snippets from organizational sources like dashboards, queries, and connected apps to provide continuously updated business context.
OntoRank ranks these sources by authority using signals such as certification, usage, and authorship, ensuring Genie grounds answers in the most trusted data.
Genie can search Google Docs via MCP while running live SQL analysis, combining context with fresh data to produce reports with citations, forecasting, and scheduling without manual data science intervention.
Genie Ontology uses OntoRank to rank sources by signals like certification, usage, and authorship. It starts with certified concepts from Unity Catalog and supplements with automatically learned snippets, favoring human-certified assets before exploring discovered ones.
Genie uses MCP to search live Google Drive documents and Jira tickets. It also pulls context from dashboards, notebooks, and SQL queries stored in Unity Catalog and other connected sources.
Yes, Genie One has built-in forecasting. A user can ask Genie to forecast a trend, and it will analyze usage data and flag accounts to watch without filing a separate data science request.
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