Genie
Recent items mentioning Genie across the Databricks ecosystem — releases, news, videos, and community Q&A. Updated hourly.
Databricks Genie is rapidly evolving, with new "Agent mode" capabilities closing the gap between "what" and "why" in AI/BI investigations 1 and enabling the creation of custom "skills" for consistent code generation and task automation 9. It's also expanding its reach, now empowering natural language interrogation of operational datasets for predictive quality 7 and proactive retail markdown optimization 8, while also being integrated into AI Security Governance Hubs via Agent Bricks 3. Community discussions indicate strong interest, with mentions of a Databricks Genie android app 5 and a "next generation" launch 10.
Generated daily from the 10 most recent items mentioning Genie. Click any [N] to jump to the source.
The Four-Minute Investigation: How AI/BI Genie Agent mode closes the gap between "what" and "why"
Databricks genie called on slack
I saw a linkedin post. really cool feature Slack in channel @genie and slack gives you response and act as data analyst or data scientist directly on slack But i could not find a simple documentation on databricks. I don’t want to create server-less app and databricks api using fastapi, & azure function app or aws lambda. Just a simple managed service from databricks Could someone share gitlab documentation or internal documentation lol
TutorialsHow to Build an AI Security Governance Hub with Agent Bricks
Databricks Agent Bricks enables building an AI Security Governance Hub by transforming static security playbooks into adaptive multi-agent systems. The video demonstrates combining a knowledge assistant for unstructured documents and a Genie space for structured data into a supervisor agent, then details how to tune and monitor these agents for improved performance and data privacy.
Clinical operations intelligence belongs on the Lakehouse
The Site Feasibility Workbench, an open-source Databricks App, now enables clinical trial site selection entirely within the Databricks workspace, eliminating external API calls and synchronization pipelines. This solution addresses the architectural challenge of disconnected clinical operations data, improving enrollment target attainment with TA-segmented LightGBM models and auditable SHAP-driven explanations.
Is Databricks Genie android app not available in Databricks free edition?
Anyone else deep in Databricks BI? We started a Substack – here’s this month’s coverage
Hey r/databricks, My colleague and I work in BI and started a Substack focused specifically on Databricks BI capabilities – think AI/BI Genie, dashboards, semantic layer stuff. If you’re working with Databricks on the BI/analytics side, we’d love for you to check it out.
Predictive Quality Starts Where Defect Detection Stops
Databricks Genie now enables quality leaders to interrogate their full operational dataset using natural language, synthesizing data from inspection and supplier lots in a single query. This eliminates data latency from fragmented systems, shifting quality from reactive documentation to predictive intervention for reduced scrap and improved margins.
Retail markdown optimization: from reactive markdowns to proactive
Databricks Genie for Merchandise Intelligence now enables retail CMOs to move from reactive to proactive markdown optimization. It provides instant, natural language access to synthesize critical data like trends, inventory, and pricing, allowing for earlier trend detection and improved margins.
NewsEnhancing your Skills with Databricks Genie Code
Databricks Genie Code is an agentic coding system that allows users to build custom "skills" using markdown files, enabling it to generate code and perform tasks according to specific in-house standards and conventions. These skills provide context-on-demand, ensuring repeatable and consistent output for various engineering tasks like schema documentation or metric view creation.
The next generation of Databricks Genie just launched. Here is what data engineers actually need to know.
I have been following Genie since it first launched with AI/BI last year. Back then, I honestly thought it was mostly for business users. A chatbot on top of your data that could answer basic questions in plain English. Useful, but not something I thought data engineers really needed to care much about. After seeing the new 2026 version, I completely changed my mind. Genie is no longer just a business chatbot. The biggest change is Genie Code, which is basically an AI agent designed for data professionals. It can generate pipelines, debug failures, create dashboards, monitor systems, and work directly with Lakeflow and Unity Catalog. That part caught my attention immediately because it moves beyond simple Q&A and starts touching actual engineering workflows. What surprised me most is how connected the whole system has become. It can pull context from dashboards, Genie Spaces, apps, metadata, documentation, and external systems like GitHub, Jira, and Confluence through MCP. Instead of only searching tables, it tries to understand relationships across the environment. That feels very different from the first version. The operational side is also interesting. Genie Code can monitor pipelines, investigate failures, help with DBR upgrades, and respond to issues before teams even notice them. The more I read about it, the more it felt less like a chatbot and more like an assistant sitting beside the engineering team. But honestly, the biggest takeaway for me is not the AI itself. It is what this means for data engineers. A lot of people immediately jump to “AI will replace data engineers,” but I think the opposite is happening. These systems are only as good as the data foundation underneath them. If metadata is incomplete, if tables are messy, if naming conventions are inconsistent, or if documentation is missing, the AI layer will give poor answers confidently. That means clean data modeling, governance, metadata, documentation, and data quality are becoming even more important than before. The engineers building those foundations become more valuable, not less. I think the role is slowly shifting away from spending hours writing repetitive boilerplate transformations and more toward building trustworthy, AI-ready data systems. One thing I keep noticing while learning Databricks through BricksNotes and the wider community is that the platform is moving very quickly toward AI-native data engineering. Features like Unity Catalog, Lakeflow, and now Genie all connect together. It feels like understanding metadata and governance is becoming just as important as understanding Spark itself. Also interesting that Genie now has a full mobile experience on iOS and Android. Business users can access dashboards, apps, and chat directly from their phones, which means the underlying data quality matters even more because people are going to depend on these systems everywhere, not only during work hours. Curious if anyone here is already using Genie or Genie Code in production. I would genuinely like to hear how the answer quality has been and whether your teams are changing how they approach metadata and documentation because of it.
Energy trading analytics in a real-time market
Databricks Genie now provides energy traders and portfolio managers instant, conversational access to critical trading data, eliminating the structural revenue problem caused by analytical lags in a real-time market. This enables optimal decision-making in a highly volatile, data-intensive environment with 15-minute price changes.
NewsDatabricks Genie, Unity AI Gateway, Project Glasswing, and Model Mania | AI Newsround - April 2026
Databricks Genie is now the business user home screen for Databricks, offering a unified chat interface, external knowledge store connections, and a mobile app. The Unity AI Gateway, integrated with Unity Catalog, provides comprehensive governance for agentic AI, including permissions, auditing, and policy controls for models and tools.
Operating room utilization is hiding in your scheduling data
Databricks Genie for Surgical Operations Intelligence is now available to help healthcare operations leaders close the "Operational Intelligence Gap" by enabling real-time, conversational querying of surgical scheduling data. This allows for immediate intervention on OR utilization, shifting capacity management from reactive to proactive and addressing forgone revenue and unmet patient needs.
Why telecom churn prediction misses the intervention window
Databricks Genie for Retention Intelligence helps telecom leaders act on early churn signals by providing real-time, natural language query access to customer data. This enables timely interventions, addressing the "Velocity Problem" where traditional churn models often identify at-risk customers too late.
Growth Analytics Is What Comes After Growth Hacking
Databricks AI/BI Genie resolves the fragmented data architecture bottleneck for growth analytics, enabling leaders to conversationally interrogate unified acquisition, behavioral, and revenue data. This provides a structural competitive advantage through faster spend reallocation and learning, moving beyond growth hacking to data-driven precision.
Real-world evidence for medical affairs: who can actually use it?
Databricks Genie for Medical Affairs Intelligence helps close the RWE Fluency Gap by enabling conversational querying of complex scientific questions against RWE data. Medical Affairs leaders can now generate insights in seconds, a task that previously took data scientists days.
Wealth advisor productivity starts with the client conversation
Databricks Genie for Wealth Management Intelligence is now available, enabling wealth advisors to conversationally query client data for instant, contextual answers and remove information preparation burdens. This allows advisors to shift focus from information logistics to genuine insight during client portfolio reviews, improving productivity and the quality of client conversations.
How Databricks Genie Turns Collaboration Tools into AI-Powered Intelligence Platforms
NewsDatabricks in 3 minutes. The unified data and AI platform, explained.
Databricks unifies diverse data sources into a single data lake, providing a governed platform for analytics and AI. It offers capabilities like fine-grained access control, natural language querying with AI, and company-wide intelligent agents.
Public health intelligence shouldn't require a data scientist
Databricks Genie now enables natural language access across public health datasets, delivering rapid, governed insights to improve decision-making and resource allocation. This means public health intelligence no longer requires a data scientist, accelerating real-time outbreak response and intervention.
Mean time to detect is a data access problem
Databricks Genie within Lakewatch enables natural language, agent-driven investigations to accelerate detection and response. This addresses the core issue of cross-system data integration that limits security analysts' investigation speed and effectiveness.
First-party audience data is the ad sales relationship now
Media companies can now leverage Databricks Genie for Ad Revenue Intelligence to close the "Insight Gap" and conversationally query their first-party data for audience insights. This enables VPs of Advertising Revenue to quickly understand audience composition and demonstrate post-campaign performance, crucial for winning RFPs against platforms with richer data.
Pricing for Genie Code: Cluster usage vs. LLM tokens?
Hi everyone, I’m looking into implementing **Databricks Genie Code Agent** in our workspace and I have a question regarding the billing model. My company currently keeps a cluster (SQL Warehouse) running throughout the day. When using Genie Code to ask questions or generate logic, how exactly is the cost calculated? * **Is it just the compute cost?** Since our cluster is already active, does Genie simply "consume" those existing resources to run the generated queries? * **Are there extra LLM costs?** Does Databricks charge a separate fee for the LLM tokens (input/output) used to process natural language, or is the model usage included in the platform fee? Basically, I want to know if using Genie heavily will result in a surprise bill for "AI Tokens" or if it stays within the standard DBU consumption of our active warehouses. Thanks in advance!
The Federal Data Paradox: Rich in Data, Poor in Access
Databricks Genie enables federal agencies to overcome siloed, legacy data infrastructure by providing a natural language interface for governed, real-time data access. This empowers mission experts to make faster, evidence-based decisions without requiring a technologist for every routine task.
Model Risk Governance Is Not the Same as Risk Intelligence
Databricks AI/BI Genie for Enterprise Risk Intelligence now enables conversational interrogation of governed risk data, providing instant, accurate answers for real-time risk management. This closes the intelligence gap for CROs who previously navigated complex model outputs and data systems to get specific answers on credit concentration or stress test sensitivity.
The next generation of Databricks Genie
Alert Fatigue Is a Business Risk
Lakewatch and Databricks Genie unify data for agentic, machine-speed threat detection, triage, and response, directly addressing the business risk of alert fatigue in SOCs. This new approach helps overcome fragmented telemetry and legacy SIEM architectures that create signal-to-noise challenges and limit effective threat detection.
Shipping Faster isn’t Learning Faster
Databricks AI/BI Genie for Product Intelligence ships to resolve the architectural bottleneck of slow data velocity in product organizations. VPs of Product can now instantly query complex behavioral data with conversational AI, eliminating weeks-long waits for analyst support and specialized skills.
Why Your OEE Dashboard Is Lying to You
Your OEE dashboard is likely misrepresenting operational reality because critical production data remains siloed and inaccessible. Databricks Genie provides a conversational AI layer over your unified data platform, making operational systems instantly answerable in natural language to empower real-time decision-making.
The Turbine That Tried to Tell You It Was Failing
Databricks Genie now offers a conversational AI layer for real-time operational metrics like OEE, directly accessible to VPs of Operations. This eliminates data access bottlenecks, enabling faster decision-making by shifting from reactive reports to proactive intelligence from SCADA and MES logs.
Predicting Readmissions Isn't Enough. Acting in Time Is.
Databricks Genie for Clinical Outcomes Intelligence now enables CMOs to conversationally query patient and outcomes data in natural language, providing immediate, governed insights to prevent predicted readmissions. This directly addresses the gap between readmission risk prediction and timely intervention by eliminating data request delays and matching clinical decision velocity.
Clinical Trials Run Longer Than They Have To. That's a Patient Problem
Databricks Genie for Clinical Trial Intelligence now enables clinical operations VPs to interrogate full trial data in natural language for instant answers. This allows earlier intervention on site performance issues, shortening trial timelines and improving patient access to treatment.
Network Quality Is a Revenue Problem, Not a Technical One
Databricks Genie for Network-Commercial Intelligence bridges the gap between network performance and commercial data, enabling Chief Network Officers to prioritize network quality decisions based on commercial impact. This helps reframe network quality as a revenue problem, not just a technical one, by connecting operational telemetry to commercial context like SLA exposure and churn propensity.
Databricks Genie app
The Databricks Genie app is available on the Play Store!
[FREE WEBINAR] Running Supply Chain Operations on Databricks: From Dashboards to Agents (BrickTalk)
Hey r/Databricks! We're hosting a free community sponsored BrickTalk this Thursday, May 7th, focusing on modern Supply Chain Management using Databricks. BrickTalks is a community event series where Databricks experts share real-world use cases, demos, and practical insights for building with data and AI, giving customers a direct line to the people behind the products. Discover how to build a unified Control Tower that delivers real-time inventory visibility, AI-powered demand forecasting, and autonomous planning. We'll demo an end-to-end operational platform featuring Databricks AI/BI Genie Rooms and multi-agent Supervisor workflows. You'll see: * Dashboards surfacing key insights. * Genie answering natural language queries grounded in live data. * Agentic systems autonomously processing inbound requests to generate fulfillment plans. This is a great chance to see real-world use cases and get practical insights directly from Databricks experts. **When:** Thursday, May 7 * 9:00 am PT * 12:00 pm ET * 5:00 pm London * 9:30 pm IST [Register here](https://usergroups.databricks.com/events/details/databricks-user-groups-bricktalks-presents-supply-chain-management-bricktalk-running-supply-chain-operations-on-databricks-from-dashboards-to-agents/) Drop any questions below! 👇
Databricks One is now renamed as Genie
TLDR: * **Account-level Genie is now GA** – a single Genie experience shared across all workspaces in an account * **Unified Genie Chat** – ask once and get answers powered by full context across your data estate, including Genie Spaces, tables, metric views, dashboards, documents, and more * **Expanded connectors and sources** – native integration with platforms like SharePoint, Confluence, Google Drive, Glean, and others * **Genie Mobile** – native iOS and Android app, currently available in private preview * **Product unification** – Databricks One has been renamed to **Genie** as the unified product brand The next generation of Databricks Genie is here - check this blog out for more details: [https://www.databricks.com/blog/next-generation-databricks-genie](https://www.databricks.com/blog/next-generation-databricks-genie)
The next generation of Databricks Genie
The new Genie can answer questions beyond the boundaries of a Genie Space, connect to enterprise knowledge sources like Google Drive and Sharepoint, and combine structured and unstructured data to generate insights. Genie now includes all capabilities previously known as Databricks One, marking a significant shift in how business users engage with the platform. Along with account-level access and native iOS and Android apps, Genie is becoming the primary way users experience Databricks - available anytime, anywhere.
The next generation of Databricks Genie
Genie now answers questions beyond Genie Spaces, connecting to external knowledge stores like Google Drive and SharePoint. This next generation of Genie, previously Databricks One, is available on web and native mobile apps.
How conversational analytics removes the BI bottleneck
Databricks Genie and Lakebase are transforming BI by enabling conversational analytics with enterprise context, providing actionable insights beyond traditional dashboards. Operationalizing trusted AI-powered analytics, built on robust governance and semantic layers, is now crucial to avoid a competitive gap.
How to transform document activation workflows with Genie and Agent Bricks
Databricks shipped a solution combining AI/BI Genie, Agent Bricks, and Unity Catalog to automate document activation workflows. This enables multi-agent orchestration for extracting, processing, and activating data from diverse documents, improving efficiency and governance.
NewsAsk Genie Anywhere | Bring AI/BI Genie to Microsoft Teams & M365 Copilot via Copilot Studio
Databricks' AI/BI Genie, a data analyst agent, now integrates natively with Microsoft Copilot Studio, allowing organizations to embed Genie into Microsoft Teams, M365 Copilot, and SharePoint. This enables users to ask data questions and receive insights directly within their collaboration tools, without leaving their workflow.
EventsHow Databricks Manages Enterprise Data and AI | Ali Ghodsi at HumanX
Databricks centralizes an organization's data from various systems into a Lakehouse, securing it and setting access rules. This consolidated and secured data then feeds into AI agents, models, and analytics for business forecasting and insights.
EventsSolving the AI Reliability Gap | Ali Ghodsi at HumanX
AI agents currently struggle with end-to-end tasks due to a lack of context, not intelligence. Addressing this reliability gap requires capturing context and changing organizational processes, a multi-year effort that Databricks is focused on.
EventsThree Things Required for Deeper Insights from AI | Ali Ghodsi at HumanX
Databricks enables deeper AI insights by combining agents and AI with a robust database and an analytics platform. This approach allows enterprises to leverage their proprietary data for predictive analytics beyond what traditional SaaS applications offer.
EventsAI Productivity and the PC Revolution Analogy | Ali Ghodsi at HumanX
AI offers 20-30% immediate productivity gains, especially in coding, but its full potential is hindered by a lack of context. Achieving greater automation requires re-engineering entire enterprise processes, similar to how early PC users initially treated them as typewriters before fully integrating them.
EventsHow Databricks Genie is Transforming Data Analysis in Minutes | Ali Ghodsi at HumanX
Databricks Genie allows scientists to quickly query complex data, like adverse effects in obesity studies, receiving accurate, referenced answers in minutes instead of months. Businesses like EasyJet use Genie to build agents that combine real-time data on seat availability, competitive pricing, and demand to dynamically set prices, a process that previously took months.
EventsHow Novo Nordisk Uses Databricks Genie for Research | Ali Ghodsi at HumanX
Novo Nordisk utilizes Databricks Genie to enable its scientists to query data warehouses and databases. This allows researchers to ask complex questions about studies, such as adverse effects, and receive accurate, statistically referenced answers.
ReleasesDatabricks Genie Code, Carl, Bull**** Bench & more! | AI Newsround - March '26 | Advancing Analytics
The video discusses Databricks' new AI tools, Genie Code for autonomous data work and Carl for faster, cost-efficient enterprise knowledge agents using custom reinforcement learning. It also covers the Bench V2 for evaluating AI models' ability to detect and push back on nonsense, along with updates to various models like Qwen 3.5, Gemini 3.1 Flashlight, and OpenAI's GPT-5.3 Instant, 5.4, Mini, and Nano, highlighting their focus on agent capabilities and cost-efficiency.
NewsDatabricks: What’s new in October 2025 #databricks news
Databricks introduces Databricks One, a new business-focused experience with consumer access for dashboards and Genie, alongside updates to Genie for defining relations and extended API endpoints. The platform also adds features like easy conversion of external to managed tables, enhanced Databricks Asset Bundles with policy integration and script execution, and new system tables for MLflow tracking and data classification results.
Tutorials47 AIBI Genie Space in Databricks | Use Natural Language to Query data
Events[Demo] How Business Users Can Dive into Genie Deep Research
The video demonstrates how Databricks Genie's deep research mode allows business users to ask complex questions, generating a research plan that can be reviewed and executed. Genie then performs parallel analysis, providing a summarized answer with actionable insights and traceable citations for each step of its research.
