Join industry pioneers Boeing and CARIAD (Volkswagen Group) as they showcase how advanced data platforms are revolutionizing mobility across air and ground transportation. Boeing's Jeppesen Smart NOTAMs system demonstrates the power of compound AI in aviation safety, processing over 4.5M critical flight notices annually and serving 75% of commercial aviation through an innovative combination of MLflow, GenAI, and Delta Sharing technologies. CARIAD follows with insights into their groundbreaking Unified Data Ecosystem (UDE), the singular data platform powering Volkswagen Group's global mobility transformation across all brands and markets. Together, these leaders illustrate how smart data architecture is building the foundation for the future of transportation, from the skies to the streets.

Are you striving to build a data-driven culture while managing costs and reducing reporting latency? Are your BI operations bogged down by complex data movements rather than delivering insights? Databricks IT faced these challenges in 2024 and embarked on an ambitious journey to make Databricks AI/BI our enterprise-wide reporting platform. In just two quarters, we migrated 2,000 dashboards from a traditional BI tool — without disrupting business operations. We’ll share how we executed this large-scale transition cost-effectively, ensuring seamless change management and empowering non-technical users to leverage AI/BI. You’ll gain insights into: Key migration strategies that minimized disruption and optimized efficiency Best practices for user adoption and training to drive self-service analytics Measuring success with clear adoption metrics and business impact Join us to learn how your organization can achieve the same transformation with AI-powered enterprise reporting.

The GTM team at Databricks recently launched the GTM Analytics Hub—a native AI/BI platform designed to centralize reporting, streamline insights, and deliver personalized dashboards based on user roles and business needs. Databricks Apps also played a crucial role in this integration by embedding AI/BI Dashboards directly into internal tools and applications, streamlining access to insights without disrupting workflows. This seamless embedding capability allows users to interact with dashboards within their existing platforms, enhancing productivity and collaboration. Furthermore, AI/BI Dashboards leverage Databricks' unified data and governance framework. Join us to learn how we’re using Databricks to build for Databricks—transforming GTM analytics with AI/BI Dashboards, and what it takes to drive scalable, user-centric analytics adoption across the business.

Tired of data silos and the constant need to move copies of your data across different systems? Imagine a world where all your enterprise data is readily available in Databricks without the cost and complexity of duplication and ingestion. Our vision is to break down these silos by enabling seamless, zero-copy data sharing across platforms, clouds, and regions. This unlocks the true potential of your data for analytics and AI, empowering you to make faster, more informed decisions leveraging your most important enterprise data sets. This session you will hear from Databricks, SAP, and Salesforce product leaders on how zero-copy data sharing can unlock the value of enterprise data. Explore how Delta Sharing makes this vision a reality, providing secure, zero-copy data access for enterprises.SAP Business Data Cloud: See Delta Sharing in action to unlock operational reporting, supply chain optimization, and financial planning. Salesforce Data Cloud: Enable customer analytics, churn prediction, and personalized marketing.

In the complex world of logistics, efficiency and accuracy are paramount. At Pilot, the largest travel center network in North America, managing fuel delivery operations was a time-intensive and error-prone process. Tasks like processing delivery records and validating fuel transaction data posed significant challenges due to the diverse formats and handwritten elements involved. After several attempts to use robotic process automation failed, the team turned to Generative AI to automate and streamline this critical business process. In this session, discover how Pilot leverages GenAI, powered by advanced text and vision models, to revolutionize BOL processing. By implementing few-shot learning and vectorized examples, the data team at Pilot was able to increase document parsing accuracy from 70% to 95%, enabling real-time validation against truck driver inputs, which has resulted in millions of savings from accelerating credit reconciliation and improved financial operations.

AI agent systems hold immense promise for automating complex tasks and driving intelligent decision‑making, but only when they are engineered to be both resilient and transparent. In this session we will explore how Dataiku’s LLM Mesh pairs with Databricks Mosaic AI to streamline the entire lifecycle: ingesting and preparing data in the Lakehouse, prompt engineering LLMs hosted on Mosaic AI Model Serving Endpoints, visually orchestrating multi‑step chains, and monitoring them in real time. We’ll walk through a live demo of a Dataiku flow that connects to a Databricks hosted model, adds automated validation, lineage, and human‑in‑the‑loop review, then exposes the agent via Dataiku's Agent Connect interface. You’ll leave with actionable patterns for setting guardrails, logging decisions, and surfacing explanations—so your organization can deploy trustworthy domain‑specific agents faster & safer.

XP is one of the largest financial institutions in Brazil– and they didn’t reach that scale by moving slowly. After getting inspired at Data + AI Summit in 2024, they sprang into action to overhaul their advertising strategy using their first-party data in Databricks. Just a year later, they’ve achieved remarkable success: they’ve unlocked $66 million in incremental revenue from advertising, with the same budget as before. In this session, XP will share the tactical steps they took to bring a first-party data and AI strategy to customer acquisition– including how they built predictive models for customer quality and connected Databricks to their ecosystem through Hightouch’s Composable CDP. If you’re supporting an advertising team or are looking for real strategies to take home from this conference that can transform your business: this session is for you.

Think Databricks is just for data and models? Think again. In this session, you’ll see how to build and scale a full-stack AI app capable of handling thousands of queries per second entirely on Databricks. No extra cloud platforms, no patchwork infrastructure. Just one unified platform with native hosting, LLM integration, secure access, and built-in CI/CD. Learn how Databricks Apps, along with services like Model Serving, Jobs, and Gateways, streamline your architecture, eliminate boilerplate, and accelerate development, from prototype to production.

DSPy is a framework for authoring GenAI applications with automatic prompt optimization, while MLflow provides powerful MLOps tooling to track, monitor, and productize machine learning workflows. In this lightning talk, we demonstrate how to integrate MLflow with DSPy to bring full observability to your DSPy development. We’ll walk through how to track DSPy module calls, evaluations, and optimizers using MLflow’s tracing and autologging capabilities. By the end, you'll see how combining these two tools makes it easier to debug, iterate, and understand your DSPy workflows, then deploy your DSPy program — end to end.

In an era where insights-driven decision-making is paramount, the insurance industry stands at the cusp of a major technological revolution. This session will delve into how Agentic AI — AI agents act autonomously to achieve critical goals — can be leveraged to transform insurance operation (underwriting, claims, services), enhance customer experiences and drive strategic growth.

The Databricks ecosystem has 5,000+ partners, who help enable you to leverage Databricks to unify all your data and AI workloads for more meaningful insights. Hear from some of the leading cloud, technology, and consulting partners.

SAP is the world's 3rd-largest publicly traded software company by revenue, and recently launched the joint SAP Databricks "Business Data Cloud". See how it all works from a practitioner's perspective, including reference architecture, demo, and example customers. See firsthand how the powerful suite of SAP applications benefits from a joint Databricks solution - with data being more easily governed, discovered, shared, and used for AI/ML..

FunPlus's journey to building a cost-effective and efficient data platform with Databricks: exploring how FunPlus leveraged Databricks to tackle key challenges, enhance data engineering and ML efficiency, and showcasing best practices and their impact on game development and operations.

Agents solve complex problems, but building them can be hard. This talk will walk through techniques to build effective multi-agent networks in production deterministically, reducing the compounding error rates across each AI call.

Are data teams ready for AI? Prophecy’s exclusive survey, “The Impact of GenAI on Data Teams”, gives the clearest picture yet of GenAI’s potential in data management, and what’s standing in the way. The top two obstacles? Poor governance and slow access to high-quality data. The message is clear: Modernizing your data platform with Databricks is essential. But it’s only the beginning. To unlock the power of AI and analytics, organizations must deliver governed, self-service access to clean, trusted data. Traditional data prep tools introduce risks around security, quality, and cost. It’s no wonder data leaders cited data transformation as the area where GenAI will make the biggest impact. To deliver what’s needed teams need a shift to governed self-service. Data analysts and scientists move fast while staying within IT’s guardrails. Join us to learn more details from the survey and how leading organizations are ahead of the curve, using GenAI to reshape how data gets done.

GenAI systems are evolving beyond basic information retrieval and question answering, becoming sophisticated agents capable of managing multi-turn dialogues and executing complex, multi-step tasks autonomously. However, reliably evaluating and systematically improving their performance remains challenging. In this session, we'll explore methods for assessing the behavior of LLM-driven agentic systems, highlighting techniques and showcasing actionable insights to identify performance bottlenecks and to creating better-aligned, more reliable agentic AI systems.

Join us to see how the powerful combination of ThoughtSpot's agentic analytics platform and the Databricks Data Intelligence Platform is changing the game for data-driven organizations. We'll demonstrate how DataSpot breaks down technical barriers to insight. You'll learn how to get trusted, real-time answers thanks to the seamless integration between ThoughtSpot's semantic layer and Databricks Unity Catalog. This session is for anyone looking to leverage data more effectively, whether you're a business leader seeking AI-driven insights, a data scientist building models in Python, or a product owner creating intelligent applications.

The ability for different AI systems to collaborate is more critical than ever. From traditional ML development to fine-tuning GenAI models, Databricks delivers the stability, cost-optimization and productivity Expedia Group (EG) needs. Learn how to unlock the full potential of AI interoperability with Databricks. AI acceleration: Discover how Databricks acts as a central hub, helping to scale AI model training and prediction generation to deliver high-quality insights for customers. Cross-platform synergy: Learn how EG seamlessly integrated Databricks' powerful features into its ecosystem, streamlining workflows and accelerating time to market. Scalable deployment: Understand how Databricks stability and reliability increased efficiency in prototyping and running scalable production workloads. Join Shiyi Pickrell to understand the future of AI interoperability, how it’s generating business value and driving the next generation of travel AI-powered experiences.

In an era of skyrocketing content volumes, companies are sitting on huge libraries — of video, images and audio — just waiting to be leveraged to power targeted advertising and recommendations, as well as reinforce brand safety. Coactive AI will show how fast and accurate AI-driven metadata enrichment, combined with Databricks Unity Catalog and lakehouse, is accelerating and optimizing media workflows. Learn how leading brands are using content metadata to: Unlock new revenue through contextual advertising Drive personalization at scale Enhance brand safety with detailed, scene-level analysis Build unified taxonomies that fuel cross-functional insights Transform content from a static asset into a dynamic engine for growth, engagement and compliance.

Discover how to build and deploy AI-powered applications natively on the Databricks Data Intelligence Platform. This session introduces best practices and a standard reference architecture for developing production-ready apps using popular frameworks like Dash, Shiny, Gradio, Streamlit and Flask. Learn how to leverage agents for orchestration and explore primary use cases supported by Databricks Apps, including data visualization, AI applications, self-service analytics and data quality monitoring. With serverless deployment and built-in governance through Unity Catalog, Databricks Apps enables seamless integration with your data and AI models, allowing you to focus on delivering impactful solutions without the complexities of infrastructure management. Whether you're a data engineer or an app developer, this session will equip you with the knowledge to create secure, scalable and efficient applications within a Databricks environment.