{"slug": "introducing-genie-one-genie-agents-and-genie-ontology", "title": "Introducing Genie One, Genie Agents, and Genie Ontology", "summary": "Databricks announced Genie One, Genie Agents, and Genie Ontology, a data-smart AI coworker grounded in enterprise context, to help teams get accurate insights from business data. The new tools embed into Slack and Microsoft Teams, offer mobile apps, and allow users to create domain-specific agents from a single prompt.", "body_md": "The data-smart AI coworker, grounded in your enterprise context.\n\nby [Sydney Sundell](/blog/author/sydney-sundell), [Ken Wong](/blog/author/ken-wong) and [Elise Georis](/blog/author/elise-georis)\n\nDespite the progress in LLMs and consumer chat agents, most enterprise teams still struggle to put AI to work on real business questions. The reason is that getting insights out of data - the ground truth of the business - is hard even with the latest generations of models and agents.\n\nThe reason for this is that the business context required to use data is scattered across dashboards, queries, pipelines, wikis, tickets, documents, and chat threads. When AI doesn’t easily find the information it needs, it fills in the gaps with inference, producing answers that are generic at best and wrong at worst. The current generation of agents often go through a process of iterative probing that is extremely slow and costly, and forcing a compromise in quality. This has resulted in [unacceptably poor performance](https://www.databricks.com/blog/pushing-frontier-data-agents-genie) for truly data-driven decision making and actions.\n\nToday, we are announcing our solution to this problem:\n\nGenie began as a conversational analytics assistant in Databricks AI/BI. [Genie One](https://www.databricks.com/product/genie/one) is the next step: a data-smart AI coworker designed to help users move from insight to action.\n\nBecause enterprise work happens across a full stack of tools and surfaces, we’re bringing Genie to everywhere work happens—starting by embedding it natively into [Slack](https://docs.databricks.com/aws/en/genie-ui/genie-slack) and [Microsoft Teams](https://learn.microsoft.com/en-us/azure/databricks/integrations/msft-teams). Users can simply @mention Genie in any conversation to ask questions in natural language and get accurate answers in seconds. Genie can also be used in public channels and threads, helping teams collaborate without switching context. Every response is governed, secure, and tailored to what each user is authorized to access.\n\nFor users on the go, we’re launching new [iOS ](https://apps.apple.com/lk/app/databricks-genie/id6758961415)and [Android](https://play.google.com/store/apps/details?id=com.databricks.one.mobile&hl=en_US) apps that put Genie in your pocket. Users can ask questions, get alerts, and take action on insights grounded in your company data, from anywhere.\n\nAnd for organizations who have adopted an existing AI agent or developed their own, we’re also announcing the Genie MCP App, which allows those users to benefit from Genie without having to change their workflows.\n\nOur investment in building the Uplight Data Platform on top of Databricks is paying off in powerful new ways. By bringing Genie One capabilities to our data, we’re enabling teams across Uplight to explore, discover, and innovate with more speed, confidence, and creativity than ever before. This is the promise of data democratization - enabling a culture where curiosity, data-informed decision-making, and innovation can happen at every level of the company.— Micaela Christopher, Director of Data Science and Engineering, Uplight\n\nDatabricks customers have created more than a million Genie Spaces—curated, governed chat experiences scoped to specific topics, with verified logic and benchmarks. Now, **Genie Spaces is evolving into Genie Agents**: curated, domain-specific AI agents that:\n\nBest of all, creating an agent is as simple as describing what you want: **spin up a Genie Agent from a single prompt** in Genie One or Genie Code, scope it, benchmark it, and share it for teammates to use or customize. Genie Agents let domain experts scale their expertise by turning trusted rules, data, and workflows into coworkers the whole team can rely on.\n\nAt Foot Locker, Genie Agents are transforming how we lead. They provide our executives and business teams with a centralized space to harness AI-driven insights across every North American banner we operate. As we scale Genie to the enterprise, it's reshaping the way our business interacts with data and makes the decisions that matter most. Genie isn't just a tool; it's the engine driving self-service insights across our organization— Matt Giunipero, VP of Data & Analytics and Krish Lakshminarayanan, VP, AI, Data & Analytics, Enterprise Architecture, Foot Locker\n\nGenie One and Genie Agents are powered by **Genie Ontology**, an automatic context layer. Genie Ontology automatically extracts snippets of knowledge from tables, queries, dashboards, pipelines, and connected apps, and organizes that knowledge into a living graph of how a company works and what the data inside *actually *means. Genie has context about where to look, what to trust, and how to answer in a way that reflects how the company actually uses its data. That includes metric definitions, business terms, unique calculations, and the relationships between concepts, metrics, tables, and teams.\n\nOne key innovation of Genie Ontology is its approach to determining authority. Using an approach similar to PageRank, Genie Ontology weighs where a definition came from, the relative authority of that source’s author, how often people rely on it, how closely it ties to certified and widely-used assets, and how fresh it is. Then, Genie answers from the sources that carry the most weight. It also enforces the permissions of each source by only showing you the content that you actually have permissions to see. The result is that Genie solves the context problem, without asking your teams to hand-curate it or manage a separate permissions system.\n\nOur internal benchmark of real-world enterprise data analysis tasks have shown that Genie Ontology significantly improves agent performance on complex, enterprise data questions. In our testing, Genie answered **84.5%** of questions correctly on the first attempt, while the strongest general-purpose coding agent managed just **52.4%** — and the weakest only **25%**. And Genie doesn’t trade off accuracy for speed. Genie delivers high accuracy *and* low latency, 2× faster than the strongest coding agent.\n\nTo roll out any AI tool across a company, leaders and IT teams need confidence that it’s governed, secure, and ready to scale. That’s why Genie One includes a full suite of admin governance tools designed to help organizations deploy AI across their teams.\n\nLike every Databricks product, governance and security sit at the heart of Genie. Permissions are enforced by default on every answer through source-native ACLs or Unity Catalog. MCP, tools and costs are governed by the **Unity AI Gateway**, providing a single pane of governance for admins.\n\nGetting started\n\nGenie One is the data-smart AI coworker every business user needs: it understands enterprise context, works across the tools where work happens, and is governed by design.\n\nTo try Genie One, see our [documentation](https://docs.databricks.com/gcp/en/genie-ui/genie), install the mobile app for [iOS](https://apps.apple.com/hu/app/databricks-genie/id6758961415) or [Android](https://play.google.com/store/apps/details?id=com.databricks.one.mobile&hl=en_US), or contact your Databricks account team.\n\nSubscribe to our blog and get the latest posts delivered to your inbox.", "url": "https://wpnews.pro/news/introducing-genie-one-genie-agents-and-genie-ontology", "canonical_source": "https://www.databricks.com/blog/introducing-genie-one-genie-ontology-and-genie-agents", "published_at": "2026-06-16 12:45:00+00:00", "updated_at": "2026-06-16 13:23:26.009158+00:00", "lang": "en", "topics": ["artificial-intelligence", "ai-products", "ai-tools", "large-language-models", "ai-agents"], "entities": ["Databricks", "Genie One", "Genie Agents", "Genie Ontology", "Slack", "Microsoft Teams", "Uplight", "Foot Locker"], "alternates": {"html": "https://wpnews.pro/news/introducing-genie-one-genie-agents-and-genie-ontology", "markdown": "https://wpnews.pro/news/introducing-genie-one-genie-agents-and-genie-ontology.md", "text": "https://wpnews.pro/news/introducing-genie-one-genie-agents-and-genie-ontology.txt", "jsonld": "https://wpnews.pro/news/introducing-genie-one-genie-agents-and-genie-ontology.jsonld"}}