Summary:
Databricks, a data and AI company, announced Genie One, an all-new agentic coworker that helps business teams automate and orchestrate their work across any data — structured or unstructured, analytical or operational, inside or outside Databricks.
Genie One is part of Genie, Databricks’ suite of AI coworkers that turn business data into trusted answers and actions.
At the core of the Genie family is Genie Ontology, a web of all knowledge in an organization from everyone and everything, including data, docs, tags, content, apps, documents, and people. It is a new self-improving context layer that solves one of enterprise AI’s hardest problems: understanding a business completely from its data, so AI can be smarter and more effective. Genie Ontology automatically extracts and continuously updates business knowledge from Databricks as well as AI tools and connected workplace apps across files, tickets, chats, and meetings. Now, with this ground truth, Genie can retrieve real answers from governed data and take the right next action, rather than guess from incomplete context. The result is higher accuracy, reduced latency, and lower costs.
With Genie Agents and Genie App Builder, teams across the business can create reusable agents and applications — all connected to their data with access controls, permissions, and cost governance built in.
Why Early Enterprise AI Coworkers Have Fallen Short
AI transformed software engineering because the context engineers need lives in one place: the source code. It’s complete, structured, and easy for agents to read. The rest of the enterprise hasn’t seen the same transformation, because most business work isn’t like that. The context is scattered across different systems, and much of what matters lives only in people’s heads. Business teams want to ask simple questions about how the company is doing and act on the answers, but even the best AI agents can’t answer reliably when the information is fragmented and undocumented. When context is missing, AI fills the gap with guesses. And in finance, operations, or sales, a confident wrong answer is often worse than no answer at all.
Closing the AI Context Gap
Genie solves this by treating governed enterprise data, not documents or embeddings, as the ground truth. Genie Ontology continuously extracts and updates business context from across Databricks and connected systems, so Genie One can look up the real answer to business questions in curated, authoritative data through SQL rather than reason from fragments spread across documents. The result is a data-smart agentic coworker that can explain why margins changed, surface upsell opportunities in a sales pipeline, or help finance close the books, because it’s working from the same data on which the business actually runs.
“Most enterprise AI today is just guessing with false confidence. That is not good enough for business,” said Ali Ghodsi, co-founder and CEO, Databricks. “If you’re a CFO and AI can’t tell you why margins changed, or you’re a sales leader, and it can’t find your next upsell, that’s not an AI problem, that’s a context problem. Genie Ontology continuously learns context from data everywhere, so our answers are much faster and our agents are more accurate. That’s the difference between an AI chatbot and an agentic coworker who knows your business inside out — every metric, every data source, every answer. Every CEO and business leader should have Genie at their fingertips.”
Additional Details
“Albertsons Companies is building Merchandising Intelligence to help merchants make faster, more explainable, and more customer-relevant decisions across the 4Ps (product, pricing, promotions, and placement) of merchandising. The initiative brings together trusted enterprise data, merchant expertise, and AI-enabled insights to help teams better understand customer needs and create a more consistent shopping experience. Databricks provides a core foundation for this capability through the Lakehouse, Unity Catalog, AI Gateway, and Genie – supporting governed data, scalable analytics, trusted AI access, and merchant-friendly discovery in one platform. Genie plays an important role in making complex merchandising data easier for merchants to explore and understand in natural language, while the broader Databricks platform supports the end-to-end intelligence layer needed to move from data discovery to explainable recommendations and action,” said Karthik Iyer, group VP, head, merchandising, transformation, and AI, Albertsons.
“Our 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,” added Micaela Christopher, director, data science and engineering, Uplight.
“At 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,” concluded Krish Lakshminarayanan, VP, AI, data & analytics, enterprise architecture, and Matt Giunipero, VP, data & analytics, Foot Locker.
Availability
Genie has no seat-based pricing and organizations get up to $10 free for every user every month, so organizations pay only for the AI actually used. Genie One, Genie Agents, and Genie Code are now generally available. Genie App Builder and Genie ZeroOps will enter private preview shortly after the Data + AI Summit. Genie is now available as native iOS and Android apps.
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