Despite 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.

The 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 for truly data-driven decision making and actions.

Genie began as a conversational analytics assistant in Databricks AI/BI. Genie One is the next step: a data-smart AI coworker designed to help users move from insight to action.

Because 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 and Microsoft 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.

For users on the go, we’re launching new iOS and Android 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.

And 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.