Databricks unveils Genie One agentic AI coworker to automate business workflows across teams

Databricks' new agentic coworker Genie One brings AI automation to every part of the business

Databricks' new agentic coworker Genie One brings AI automation to every part of the business Big data company Databricks Inc. is getting into the agentic artificial intelligence coworker game with the launch of a new tool called Genie One, aimed at helping business teams orchestrate workflows and automate work-related tasks. The arrival of Genie One expands on the company's existing Genie suite, but goes well beyond its original conversational analytics capabilities. Instead of simply digging into data for answers, it provides comprehensive assistance by doing things on behalf of workers. It reasons over both structured and unstructured data, including corporate information that lives outside the Databricks platform. Genie One was announced during the company's annual Data + AI Summit, which kicked off in San Francisco today. At the event, it also announced a new architecture called Lake Transactional/Analytical Processing that unifies data from operational and analytical workloads within a single data lake. Co-founder and Chief Executive Ali Ghodsi said Genie One is an effort to help enterprises overcome their frustrations with existing AI copilot tools, which have failed to live up to their extraordinary early promises. While AI has had a significant impact on software engineering teams, that's only because AI coding tools had the fortune of having the required context buried within the source code they're working on. But other business workloads don't have the same luxury. When it comes to things like sales, marketing and finance, the critical business context needed to automate tasks is highly fragmented - it's there, but it's buried deep and scattered far and wide across disparate software platforms, year-old business documents or even locked inside the heads of employees. The challenge is that standard AI agents tend to take a holistic view of businesses, which means they struggle to answer simple business questions reliably, let alone actually automate work. If the context isn't there, many AI tools simply hazard a guess in order to try and fill in the blanks, which can be disastrous in highly-regulated fields such as finance and operations. Genie One has no such problems thanks to Genie Ontology, which is a self-improving context layer that maps the extent of an organization's knowledge by scanning all of its business data, documents, content, applications and even by learning from its people. Genie Ontology is what allows the new assistant to understand a business much more thoroughly. It continuously extracts business knowledge from every source its given permission to access, including Databricks itself and others such as connected workplace applications, files, tickets, chat apps and meetings. With this embedded "ground truth," Genie One can create answers grounded in real and reliable business knowledge, which means it can take the right action instead of guessing. As a result, Ghodsi insisted it's much more accurate, with lower latency and costs. "Most enterprise AI today is just guessing with false confidence, but that is not good enough for business," he said. "If you're a CFO and AI can't tell you why margins have changed, or you're a sales leader and it can't find your next upsell, that's not an AI problem, it's a context problem. Genie Ontology continuously learns context from data everywhere, so our answers are much faster and our agents are more accurate." Genie One works by fetching the necessary context via Structured Query Language queries, rather than trying to reason over a few fragmented documents and likely hallucinating. It does much more than just answer questions, though - in addition, it comes with visual interfaces such as interactive charts, enabling users to set up alerts. Then, through its integration with the Model Context Protocol, it can use third-party software and tools to take actions within any business workflow. Customers will also be able to access the first Genie Agents, which are being launched in general availability today alongside Genie One. Users can transform any conversation with Genie, the company's original AI chatbot, into "reusable agents" that inherit the original source data, instructions and behavior. Workers can then use these agents to execute repeatable workflows and accelerate their productivity. Elsewhere, there's a new Genie App Builder that provides a comprehensive vibe coding environment for business workers to upload context and generate a preview of an application connected to that data, fully secured by the Databricks Unity Catalog. Finally, the company updated Genie Code and introduced Genie ZeroOps for data engineers. The first is a tool that helps data engineers to plan, create and run data engineering and analytics workflows. It's getting the additional ability to track progress and review each step in different projects. Meanwhile the latter is a new background agent designed to autonomously monitor, investigate and propose fixes for things like data pipelines, tables, machine learning models and more. Databricks said it's eschewing the traditional software-as-a-service licensing model for Genie One in favor of more straightforward pay-as-you-go-pricing, where customers pay for the tokens they consume.

Databricks Launches Agentic Coworker Fueled by All Business Data | PYMNTS.com

Genie One is the successor to the first generation of Genie, which only used data stored on Databricks. With the additional data it can access, Genie One can be used by marketing, finance, sales and other business teams, Databricks said in a Tuesday (June 16) press release. Like the other artificial intelligence coworkers offered by Databricks, Genie One is powered by Genie Ontology, a context layer that automatically extracts business knowledge from Databricks, AI tools and connected workplace apps, according to the release. "Genie Ontology continuously learns context from data everywhere, so our answers are much faster and our agents are more accurate," Databricks Co-Founder and CEO Ali Ghodsi said in the release. "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." Databricks also introduced Genie Agents, which allow teams to save any Genie conversation as a reusable agent; Genie App Builder, which provides a fully managed vibe coding environment; Genie Code, which helps teams plan, build and run data engineering, machine learning and analytics workflows; and Genie ZeroOps, which monitors, investigates and proposes fixes for data and AI assets. Genie One, Genie Agents and Genie Code are generally available, while Genie App Builder and Genie ZeroOps will soon enter private preview, per the release. Databricks said in February that it secured $7 billion in new investments and would use the new capital to bolster Lakebase, which is the company's serverless Postgres database for AI agents, and Genie. "With this new capital, we'll double down on Lakebase so developers can create operational databases built for AI agents," Ghodsi said at the time in a press release. "At the same time, we're investing in Genie to let every employee chat with their data, driving accurate and actionable insights." It was reported June 8 that Databricks has discussed a funding round that could begin within the next month and value the company at between $165 billion and $175 billion. It was most recently valued at $134 billion.