Genie

What Is – Genie One MCP? (A phone line to your data's front desk)

Genie One docs can be co-edited now

You can share a Genie One document and anyone with CAN EDIT can work on it with you. Genie also reuses similar past investigations so you are not re-explaining the same question every week. Handy for Monday ops reviews. Last week's fill-rate thread comes back, you drop the one-pager in the canvas, share it with the planner, and they tweak the filters themselves instead of Slack-pinging for another screenshot. https://docs.databricks.com/aws/en/genie-one/documents#share submitted by /u/Wise_Ear_4064 [link] [comments]

Dashboard Insights: Genie summarizes the charts

Viewers of a published dashboard can have Genie analyze a page’s charts and return insight cards that call out trends and outliers. It uses the dashboard’s Genie Agent (Settings → General → Enable Genie). Ask Genie only works in basic embedding. This is super helpful when you want insights from the visualization itself rather than general data that surrounds the dashboard. "Why is the daily revenue trend dipping in middle May?" It also saves on token cost because context is prebuilt for Genie. https://preview.redd.it/h4j90r2p1fyh1.png?width=2298&format=png&auto=webp&s=88702e4a4332618d10c3702de5e44753801ff97b https://preview.redd.it/zrksk6qr1fyh1.png?width=884&format=png&auto=webp&s=d14b183cf21d5eb0acaf9910d4220e8e6d1ce7e8 Dashboard Insights · AI/BI note submitted by /u/Wise_Ear_4064 [link] [comments]

Genie One PDF Download Cut Off

How to retire Genie Agents and dashboards nobody uses (so you can say yes to more of them)

Asset Bundles: how to link a bundle-managed Genie space to an AI/BI dashboard across environments (o

Beyond the Dashboard: Why AI Data Assistants Fail Without Unity Catalog Governance

For years, the promise of self-service BI has been a moving target. We gave business users drag-and-drop tools, semantic layers, and natural language query bars. Yet, time and again, we hit the same wall: trust. When a business user asks an AI tool, "What was our fleet downtime last quarter?" , the AI is only as good as the underlying data fabric. If your data is trapped in fragmented silos, uncatalogued, and un-governed, conversational AI quickly becomes an expensive generator of confident misinformation. This is where the paradigm is shifting. With the introduction of tools like Databricks Genie , we are moving past rigid dashboards into the era of conversational analytics. But as Solution Architects, our job isn't just to look at the UI layer—we have to look at the spine of the architecture. Here are three architectural realities I’ve learned while implementing modern Lakehouse patterns: 1. AI Without Governance is Just Automated Chaos You cannot point an LLM at a raw storage bucket and expect accurate insights. Genie relies entirely on the metadata, table descriptions, and foreign key relationships defined in Unity Catalog . If your governance layer is messy, your AI's answers will be messy. Unity Catalog isn’t just a security tool anymore; it is the semantic foundation for enterprise AI. 2. The Shift from "Building Pipelines" to "Curating Context" Tools like Lakeflow Connect and automated ingestion frameworks are taking over the heavy lifting of ETL. As data engineers and architects, our value is no longer measured by how many custom Spark scripts we write to move data. Our value is measured by how well we curate the Gold layer —structuring tables, defining clear column descriptions, and setting up quality expectations so that tools like Genie can actually understand the domain context. 3. Real-Time Trust Beats Real-Time Speed In heavy industries—like managing IoT telemetry for gas turbines—getting data in 5 seconds doesn't matter if the data quality is flawed. Integrating Delta Live Tables (DLT) Expectations as a quality firewall before data hits the consumption layer ensures that both human analysts and AI assistants are querying verified, pristine data. The Takeaway Conversational AI and natural language agents like Genie are the future of data consumption. But they are built on a simple architectural truth: Garbage in, hallucination out. If we want business users to trust AI-driven insights, we have to start by modernizing our foundations with robust governance, automated pipelines, and strict data quality gates. Curious to hear from other architects out there: Have you started deploying conversational AI tools to business users yet? What are the biggest governance or data trust hurdles you've had to overcome? submitted by /u/SalamanderOpen859 [link] [comments]

Databricks Genie agent.

My company wants to roll out a Databricks Genie agent to around 5,000 users, with these requirements: Accuracy: Answers should consistently meet 90%+ accuracy. Reliability as data grows: The agent should not hallucinate or degrade when more tables are added. Scalability: The solution should extend from one business unit to multiple BUs. can we use genie In microsoft Teams. I’ve gone through the official Databricks documentation but haven’t found concrete guidance on achieving or measuring these. How would you approach this? Any architecture patterns, evaluation frameworks, or lessons from similar rollouts would be really helpful. submitted by /u/Limp-Hovercraft7990 [link] [comments]

Genie App Builder

I'm building an app using the Databricks Genie app builder (micro app), and I'm trying to figure out whether it's possible to grant users access to Unity Catalog (UC) tables directly from within the app. But looking at the API scopes, I guess its not possible yet. https://preview.redd.it/82hz0mr358xh1.png?width=797&format=png&auto=webp&s=f5c476db84cbfdb9ac4ea826c91857c62a5830d5 submitted by /u/9gg6 [link] [comments]

Genie One Answers Likes and Dislikes Button

Genie One Guardrails

Databricks genie code changes and dbt

Hi I created my first pipeline in Databricks that sits as a .sql file. I've broken up the code into layers (stg, marts) and its working as intended. However, when the code needs to be adjusted (e.g. business definition or logic changes), I often use the genie (it's the databricks in house agent) to help me make the changes. The problem I'm running into is that since those changes are made inside databricks, the dbt files are not adjusted. I currently update the code in databricks then paste the new adjusted code into dbt but this seems backwards to me (Also a challenge when the change ripples throughout the code so I would need to update each individual stg). I imagine the changes should initially happen in dbt then that flows into databricks. We don't have claude that can link with dbt (we're only using genie). Is there a way to link genie onto dbt or is that a limitation? Any best practices in this process I should consider implementing? submitted by /u/Takoyaki_18 [link] [comments]

What’s new in Genie One — September 2026 update ?

Databricks has introduced significant feature upgrades to Your favourite AI Co-worker: Genie One , expanding its web connectivity, third-party integrations, workspace accessibility and interactive steering controls. Integrations & Native Tooling Databricks-Provided MCP Connectors : Genie One and Genie Code natively support Model Context Protocol (MCP) connectors for tools like Google Drive, Gmail, Google Calendar, Microsoft 365, Atlassian, Slack, and GitHub. Public Web Search : Genie One can autonomously search the live web for up-to-date documentation, market trends, or release notes, providing clickable source citations. PowerPoint Support : Upload and analyze .pptx presentation files directly inside conversations. Multi-File Skills (Beta): Custom skills support nested file structures up to 3 folders deep and 50 text files/folders per skill. Real-Time Interaction & Memory Controls Backend Steering: Send real-time guidance or correction prompts to Genie One while it is generating an answer without waiting for execution to finish. Memory Confirmation Prompts (Beta) : When Genie One detects relevant facts or preferences, it prompts you to confirm, edit, or reject the suggestion before saving it to long-term memory. Pinned Chats: Pin important or active conversation threads to the top of the sidebar. Enterprise Access & Mobile Enhancements Account-Only User Access: Enterprise users registered in an Identity Provider (IdP) can access account-level Genie One without needing workspace assignments or consumer licenses. Mobile MCP Write Actions (Beta) : The Genie mobile app supports interactive write operations via connected MCP tools. Scheduled Task Push Notifications (Public Preview): Receive iOS push notifications for scheduled Genie tasks directly on mobile devices. Push notifications . The Takeaway: Transforms Genie One into an enterprise-wide AI assistant that connects natively to third-party tools, supports real-time steering, and expands access beyond individual workspace boundaries Full article 👉 https://personal.nextgenlakehouse.com/whats-new-in-genie-one-september-2026-update-347c0c08e8b7?postPublishedType=initial submitted by /u/Youssef_Mrini [link] [comments]

Your Genie Agent Passed. Who's Watching Production?

Blog post: Deploying Databricks Genie Agents/Spaces to different environments with DABs

Databricks Automation Bundles (DABs) has built-in support for deployment of Genie Agents, but there is one big problem when you need to deploy to multiple environments - the agent definition contains hardcoded table names. I wrote a blog post on why this happens and how it could be solved with PyDABs. The corresponding source code is on GitHub: https://github.com/alexott/pydabs-genie-agent-retarget and also published to PyPI as pydabs-genie-agent-retarget package so you can easily plug it in into your project. submitted by /u/Acrobatic-Room9018 [link] [comments]

Databricks Genie Ontology Explained | Demo with Databricks Product Manager

Hey everyone! Elise Georis (PM at Databricks) partnered with me to do a 35-min deep-dive (chat + demo) on Genie Ontology. We covered a lot of ground and hope you enjoy learning more about it. Some of the topics covered: -Modeled ontology: governed metric views, Pages, and domains. -Learned ontology: snippets extracted from existing assets and how teams use them. -OntoRank: authorship, popularity, and source authority. -Text-to-SQL, Model Context Protocol (MCP) connectors, and search. -Source permissions, personal memory, citations, and tool governance. -Benchmark questions, domain experts, certified assets, and rollout evaluation. -Genie Ontology best practices -Much more! PS: I really appreciate your honest feedback. Knowing what really hits home for you in this video and/or what you feel the video could have done better helps me serve you better through my content! submitted by /u/JosueBogran [link] [comments]

Databricks Genie One - Managing past conversation initiated by Databricks service principal account

Why Your Genie Space Gives Wrong Answers: A Debugging Playbook

How New Developers Learn Databricks Genie: A Practical Learning Path

Jev as Judge for Genie Agents

Disable auto-scroll on Databricks Genie Code

Databricks Genie One — How to Restrict Agent Creation and Scheduled Tasks?

We use Databricks Genie One, and some users are creating unnecessary Genie Agents and scheduled tasks. Removing Consumer access or Databricks SQL access affect users’ ability to view dashboards, run SQL queries, or use other Databricks features Questions: Can workspace admin prevent regular users from creating Genie Agents? Can scheduled-task creation be disabled while users can still chat with Genie? submitted by /u/--playground-- [link] [comments]

What Is – Genie One vs a Genie Agent vs Genie Code? (And which one is for you)

Genie spaces with DABs - how do you deal with the table ordering?

Databricks Genie App Builder is now in Beta (you can turn it on in Previews)

submitted by /u/CautiousUse8597 [link] [comments]

What's new in Databricks AI/BI (Oct 2026): multi-fact modeling, Row Zero spreadsheets, Excel Add-in GA

If you work in BI on Databricks, this monthly roundup might be useful. This month's edition covers: Relationships now support multi-table schemas and measures across fact tables with different granularities (via shared dimensions) "Ignore filters" on dashboard widgets, handy for calendar hierarchies Row Zero acquisition: spreadsheets on billions of rows with a live connection to governed data Excel Add-in is GA: browse Unity Catalog, pull metric views in as native pivot tables, and ask Genie One from inside Excel Full post: https://aibilakehouse.substack.com/p/beyond-the-star-schema-spreadsheets Disclosure: all three authors work at Databricks. Happy to answer questions or hear what you'd like covered next. submitted by /u/Good_Robin [link] [comments]

Genie Agents Added Support for MCP Servers

Databricks just added MCP servers to Genie Agents. This is super valuable and different than Genie One having access to MCP servers and let me explain why. Genie Agents are domain specific and targeted at certain business personas. Genie one is a general coworker that is anyone that is trying to improve their life with AI. So Genie Agents having the ability to answer questions about a certain domain AND having access to MCP servers like Microsoft 365, google suite, Atlassian,ect... allows domain level quetions to be answered with additional context besides structured data. It opens a whole new umbrella of questions that can be answered! I tried it out this morning and so far its just the managed MCP servers which are great but hoping they expand it to customer/external MCP. They worked exactly how expected though and better yet you can see the usage via Unity Gateway. Curious to see how others like this? Documentation linked here: https://docs.databricks.com/aws/en/genie-agents/external-tools submitted by /u/Wise_Ear_4064 [link] [comments]

CUSTOMER STORY | Headspace builds trusted AI analytics with Genie Agents on Databricks

What if Databricks Genie could do more than generate code?

Trouble while Maintaining Databricks Genie Agents (VS code extension available?)

How do you regression-test a Genie space or agent when a table or metric view changes underneath it?

Genie Agent can't be added to git repo or DAB. Nothing working.

Has anyone tried working on a Geni Agent, and then tried committing those results into git? Admittedly I'm a bit new to Databricks, and to DABs, but this story is missing, and the whole experience is quite unintuitive . Any developer generally expects to be able to commit their work to source control when they've invested their time. But I'm finding that incredibly hard, when it comes to these Genie Agents. Obviously the first thing I tried to do is clone the agent into a git-controlled folder and push it to git. That didn't work. It says the asset type is unsupported. submitted by /u/SmallAd3697 [link] [comments]

What is the most effective way to evaluate Genie Agents/ Genie Spaces.

Four Databricks Genie Controls That Don't Stop Malicious Skills

CUSTOMER STORY | PicPay automates fraud triage with Databricks Genie Agents

I am trying to build an interactive dashboard on the underlying Databricks. Which of these are the best?

I’m thinking of 4 options here 1. Build an MCP (a custom MCP) that can access custom tools on Databricks and interface it on Claude.ai or Claude desktop Advantage- Claude is very good at inferencing, multi-turn conversation and multi-step processing Disadvantage - custom MCP and tools needs to be built accurately and validated. It should have full context of schema and unity catalog Build a semi-custom MCP - this will use “askGenie “ as one of its tools with additional custom tools Advantage- complexity decreases as we leverage genie space Disadvantage- double inference by genie and Claude Use custom Databricks connector in Claude. Not sure if this uses genie and therefore double inference but it’s more reliable than custom build because this is a native offering by vendor Use only genie and build custom dashboard without needing Claude interface What’s the thought on this? submitted by /u/Bala_Devaraj [link] [comments]

Announcement | Five ways marketers can use Genie One

Announcement | The Genie One MCP is now Generally Available

Lessons learned from configuring Genie Agents

Time to Swap the Cookies for Jetfuel - New Dataset & New Databricks Genie Tutorial

Most of you know samples.bakehouse . Great for a first query. Perfect for a quick demo. But after years of cookie sales, it's a little overbaked. Time to swap the cookies for jet fuel. ✈️ Together with the OpenSky Network , I brought a full day of global air traffic to Databricks Marketplace: 696 million real ADS-B position reports, messy just like real life. Myself, I used Genie for the whole journey: EDA, data exploration, a Apache Spark Declarative Pipeline, and a Lakeflow Job. Then I went a step further and read the same Marketplace data with open-source tools only, using OpenSharing and pandas. The result is this hands-on tutorial: Marketplace + Unity Catalog: get the data as a governed table Genie Agents: find anomalies in plain English Genie Agents: explore and visualize with maps and charts Genie Code: a Spark Declarative Pipeline, bronze to gold, with data quality rules Genie Code: a Lakeflow Job with schedule, retries, and email alerts Databricks Apps: your coding agent, governed by Unity Catalog OpenSharing: the open-source client in VS Code with pandas Everything runs on Databricks Free Edition (free, no credit card). 📖 Tutorial: Databricks Genie for Data Engineers and Data Scientists 💻 GitHub: databricks/tmm/DSDE-Genie-Tutorial 🛫 Dataset: OpenSky Network full-day dataset on Marketplace What's the first thing you'd query in a day of global air traffic? P.S. For the record, we still love bakehouse! 🍪❤️ [Disclaimer: I'm one of the two people who baked it.] submitted by /u/CompetitiveBet8978 [link] [comments]

Claude Academy's Using Databricks for Data Analysis - This official documentation from Anthropic on Claude Academy for how to work with Databricks is really underwhelming, so I wanted to share a guide that properly explains everything.

Hey Databricks community! I have been working with Databricks as an admin for over 4 years and I was attempting to follow this official tutorial from Anthropic for how to connect Claude with Databricks https://academy.claude.com/tutorials/using-databricks-for-data-analysis And I encountered multiple significant frustrations with doing it, as the tutorial is very underexplained and outdated for how to get Claude working with Genie One and other functions within Databricks. Therefore, I thought this video on Youtube would be valuable content to share to help solve this problem, for other people that are encountering similar difficulties when getting these two tools connected and building out systems that work for Claude to properly interact with Databricks. Let me know if this video is helpful! submitted by /u/k_kool_ruler [link] [comments]

Unlock the Power: Databricks Genie One vs. Code and Agent