Analytical and operational use cases are starting to converge, and AI-assisted applications are accelerating the trend. Most applications require a transactional, OLTP database to power data. Hear from a Databricks expert on the latest developments and our strategy for operational data integrated into the lakehouse.

Discover how Tahoe Therapeutics (formerly Vevo) is generating gigascale single-cell data that map how drugs interact with cells from cancer patients. They are using that to find better therapeutics, and to build AI models that can predict drug-patient interactions on Databricks. Their technology enabled the landmark Tahoe-100M atlas, the world’s largest dataset of drug responses-profiling 100 million cells across 60,000 conditions. Learn how we use Databricks to process this massive data, enabling AI models that predict drug efficacy and resistance at the cellular level. Recognized as the Grand Prize Winner of the Databricks Generative AI Startup Challenge, Tahoe sets a new standard for scalable, data-driven drug discovery.

Join this session to see how you can get started with data and AI using Databricks Community Edition—free, and built for learners like you. You’ll get a first look at a unified environment where you can work with professional-grade tools to load and explore data, build notebooks, and train simple models.

Unstructured data — images, documents, videos and more — is growing in importance with AI and ML. Yet managing access control at scale is challenging. Unity Catalog Volumes offer a secure foundation, but access control has remained volume-level until now. This session introduces Volume Path Permissions, a new feature enabling fine-grained access within volumes. Expanding on Unity Catalog’s robust permission model, they let you grant privileges to users and groups based on path prefixes. We’ll cover the governance model, share examples and demonstrate how to enforce least-privilege access. By the end, you’ll know how to manage file-level access with Unity Catalog’s flexibility and control.

Our project demonstrates building enterprise AI systems cost-effectively, focusing on matching merchant descriptors to known businesses. Using fine-tuned LLMs and advanced search, we created a solution rivaling alternatives at minimal cost. The system works in three steps: A fine-tuned Llama 3 8B model parses merchant descriptors into standardized components. A hybrid search system uses these components to find candidate matches in our database. A Llama 3 70B model then evaluates top candidates, with an AI judge reviewing results for hallucination. We achieved a 400% latency improvement while maintaining accuracy and keeping costs low and each fine-tuning round cost hundreds of dollars. Through careful optimization and simple architecture for a balance between cost, speed and accuracy, we show that small teams with modest budgets can tackle complex problems effectively using this technology. We share key insights on prompt engineering, fine-tuning and cost and latency management.

Databricks’ Serverless compute streamlines infrastructure setup and management, delivering unparalleled performance and cost optimization for Data and BI workflows. In this presentation, we will explore how Nationwide is leveraging Databricks’ serverless technology and unified governance through Unity Catalog to build scalable, world-class BI solutions. Key features like AI/BI Dashboards, Genie, Materialized Views, Lakehouse Federation and Lakehouse Apps, all powered by serverless, have empowered business teams to deliver faster, scalable and smarter insights. We will show how Databricks’ serverless technology is enabling Nationwide to unlock new levels of efficiency and business impact, and how other organizations can adopt serverless technology to realize similar benefits.

Cognizant developed a GenAI-driven market intelligence chatbot for RJR using Dash UI. This chatbot leverages Databricks Vector Search for vector embeddings and semantic search, along with the DBRX-Instruct LLM model to provide accurate and contextually relevant responses to user queries. The implementation involved loading prepared metadata into a Databricks vector database using the GTE model to create vector embeddings, indexing these embeddings for efficient semantic search, and integrating the DBRX-Instruct LLM into the chat system with prompts to guide the LLM in understanding and responding to user queries. The chatbot also generated responses containing URL links to dashboards with requested numerical values, enhancing user experience and productivity by reducing report navigation and discovery time by 30%. This project stands out due to its innovative AI application, advanced reasoning techniques, user-friendly interface, and seamless integration with MicroStrategy.

Agentic AI and multimodal data are the next frontiers for realizing intelligent and autonomous business systems. Learn how Infosys innovates with Databricks for accelerating data to AI agent journey at scale across an enterprise. Hear our pragmatic capability driven approach instead of use case-based approach to bring the data universe, AI foundations, agent management, data and AI governance and collaboration under unified management.

The explosion of AI has helped make the enterprise data landscape more important, and complex, than ever before. Join us to learn how Databricks’ and Tableau’s platforms come together to empower users of all kinds to see, understand, and act on your data in a secure, governed, and performant way.

How do top leaders stay ahead in a field moving at lightning speed? Join us for a dynamic panel featuring senior women leaders in data and AI as they share reflections on their inspiring career journeys and how they’re navigating the next wave of technological transformation. These leaders are charting the course for how AI and other emerging technologies are reshaping entire industries. The conversation will offer both practical insights and personal reflections—followed by a networking reception designed to connect and further build this global community. Sponsored by EY.

Each industry has its uniqueness, and Databricks provides solutions and use cases tailored to core AI-driven industries. Hear from some of our key customers about solution accelerators and use cases across popular industries.

Databricks Apps empowers data and AI teams to easily build and deploy applications with ease - in just minutes not months! It’s the fastest and most secure way to deliver impactful solutions, with built-in governance based on Unity Catalog and the Databricks Data Intelligence Platform. See demos on the latest and greatest, and how YOU can get started right away.

Crisis Text Line has been innovating for ten years in text-based mental health crisis intervention and is now leading the next wave of GenAI use cases in the space. With over 300 million messages exchanged since 2013 and a decade of expertise, Crisis Text Line is unlocking the potential of AI to amplify human connection at a global scale.We will discuss how we leveraged our bedrock application to co-navigate crisis care through a set of early AI agent workflows. First, a simulator that reproduces texter behavior to train responders in taking conversations ranging in difficulty where the texter is in imminent risk of suicide or self-harm. Second, a tool that automatically monitors clinical quality of conversations. Third, predicted summarization to capture key context before conversations are transferred. Through the power of suggestion, this compound system aims to reduce burden and drive efficiency, such that our responders can focus on what they do best — support people in need.

This talk dives into leveraging GenAI to scale sophisticated decision intelligence. Learn how an AI copilot interface simplifies running complex Bayesian probabilistic models, accelerating insight generation, and accurate decision making at the enterprise level. We talk through techniques for deploying AI agents at scale to simulate market dynamics or product feature impacts, providing robust, data-driven foresight for high-stakes innovation and strategy directly within your Databricks environment. For marketing teams, this approach will help you leverage autonomous AI agents to dynamically manage media channel allocation while simulating real-world consumer behavior through synthetic testing environments.

“Once an idea has taken hold of the brain it's almost impossible to eradicate. An idea that is fully formed — fully understood — that sticks, right in there somewhere.” The Data Scientists and Engineers at 84.51˚ utilize the Databricks Lakehouse for a wide array of tasks, including data exploration, analysis, machine learning operations, orchestration, automated deployments and collaboration. In this talk, 84.51˚’s Data Science Learning Lead, Michael Carrico, will share their approach to upskilling a diverse workforce to support the company’s strategic initiatives. This approach includes creating tailored learning experiences for a variety of personas using content curated in partnership with Databricks’ educational offerings. Then he will demonstrate how he puts his 11 years of data science and engineering experience to work by using the Databricks Lakehouse not just as a subject, but also as a tool to create impactful training experiences and a learning culture at 84.51˚.

The new Budget Execution Validation process has transformed how the Navy reviews unspent funds. Powered by Databricks Workflows, MLflow, Delta Lake and Apache Spark™, this data-driven model predicts which financial transactions are most likely to have errors, streamlining reviews and increasing accuracy. In FY24, it helped review $40 billion, freeing $1.1 billion for other priorities, including $260 million from active projects. By reducing reviews by 80%, cutting job runtime by over 50% and lowering costs by 60%, it saved 218,000 work hours and $6.7 million in labor costs. With automated workflows and robust data management, this system exemplifies how advanced tools can improve financial decision-making, save resources and ensure efficient use of taxpayer dollars.

Healthcare and life sciences organizations are exploring AI Agents, driving transformation through intelligent supply chains to helping up-level the patient experience via virtual assistants. This session explores how you can get started with AI Agents, powered by Databricks and robust data governance, and tapping into the full potential of all your data. You’ll learn practical steps for getting started: unifying data with Databricks, ensuring compliance with Unity Catalog, and rapidly deploying AI Agents to drive operational efficiency, improve care, and foster innovation across healthcare and life sciences.

In this session, we will delve into the creation of an infrastructure, CI/CD processes and monitoring systems that facilitate the responsible and efficient deployment of Large Language Models (LLMs) at Intermountain Healthcare. Using the "AI Inventory Agents" project as a case study, we will showcase how an LLM Agent can assist in effort and impact estimates, as well as provide insights into various AI products, both custom-built and third-party hosted. This includes their responsible AI certification status, development status and monitoring status (lights on, performance, drift, etc.). Attendees will learn how to build and customize their own LLMOps infrastructure to ensure seamless deployment and monitoring of LLMs, adhering to responsible AI practices.

In capital markets, mitigating risk is critical to protecting the firm’s reputation, assets, and clients. This session highlights how firms use technology to enhance risk management, ensure compliance and safeguard operations from emerging threats. Learn how advanced analytics and machine learning models are helping firms detect anomalies, prevent fraud, and manage regulatory complexities with greater precision. Hear from industry leaders who have successfully implemented proactive risk strategies that balance security with operational efficiency. Key Takeaways: Techniques for identifying risks early using AI-powered anomaly detection. Best practices for achieving compliance across complex regulatory environments. Insights into building resilient operations that protect assets without compromising growth potential. Don’t miss this session to discover how data intelligence is transforming risk management in capital markets—helping firms secure their future while driving success!"

Marvell’s AI-driven solutions, powered by Databricks’ Data Intelligence Platform, provide a robust framework for secure, compliant and transparent Data and AI workflows leveraging Data & AI Governance through Unity Catalog. Marvell ensures centralized management of data and AI assets with quality, security, lineage and governance guardrails. With Databricks Unity Catalog, Marvell achieves comprehensive oversight of structured and unstructured data, AI models and notebooks. Automated governance policies, fine-grained access controls and lineage tracking help enforce regulatory compliance while streamlining AI development. This governance framework enhances trust and reliability in AI-powered decision-making, enabling Marvell to scale AI innovation efficiently while minimizing risks. By integrating data security, auditability and compliance standards, Marvell is driving the future of responsible AI adoption with Databricks.