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Successfully operationalizing machine learning (ML) is critical for organizations seeking to maximize the return on their initial investments. Building ML solutions in Snowflake requires not only architectural choices but also careful consideration of how to seamlessly integrate all components across the ML lifecycle. This session explores key trade-offs, lessons learned and other factors to effectively operationalize ML in Snowflake.

The presentation outlines a strategic, three-phase framework for developing data and AI solutions that yield a high return on investment. The session addresses the critical challenge that a significant majority of companies face: the inability to scale and achieve tangible value from their AI initiatives. The blueprint is valuable for attendees because it provides a clear framework for identifying a project's primary function and its associated costs, enabling them to justify scaling and ensure maximum value is realize.

Snowflake ML enables efficient development and deployment of advanced models without any data movement. With multi-GPU support, MLOps integration and Git-based workflows, Container Runtime provides a scalable environment for training, and Snowflake ML’s products such as Model Registry and Model Serving make it easy to deploy these models in production. This session explores best practices for scalable ML workflows and the creation of production-ready ML pipelines in Snowflake.

Ratepay is leveraging Snowflake's native LLM and ML features to build an automated quality assurance routine for its customer service. By ingesting knowledge base data from various sources—including emails, and images—this system automatically checks the outcome of all outgoing correspondence. This innovative approach is on track to save Ratepay significant costs by reducing reliance on external vendors and moving away from manual spot-checks. Join us to learn how to implement an automated AI-driven solution that ensures quality, reduces operational costs, and scales efficiency in customer service.

Unlock the full potential of your data. Discover how the Zero Copy integration between Salesforce Data Cloud and Snowflake creates a unified, trusted data foundation to power your AI strategy—without moving your data. We'll demonstrate how secure, governed bi-directional Zero Copy access enables real-time customer interactions and provides AI agents with the reliable context they need to succeed. Join an expert from our Munich Engineering team for an inside look at what makes Zero Copy possible: Hyper, Data Cloud's high-performance query engine, envisioned and built right here in Munich.

Snowflake is re-envisioning ease of performance in the AI era. Join us to learn about groundbreaking adaptive compute, brand new intelligent workload optimization capabilities, and industry-leading DML performance.

tesa SE is a global adhesive manufacturing company. In their highly automated tape production process it's needed to observe quality and effiency abnormal events with very short latency to avoid high costs.

Utilizing Snowflake's Machine Learning capabilities, Tesa SE is monitoring various KPI's that indicate the correct production process.

Tesa's newest innovative usecase aims to decrease waste during the production process using anomaly detection methodologies, which are trained on Snowflake, and used for inference on-edge for optimal latency.

The machine learning model pipeline components are built and served leveraging Snowflake features such as Snowflake CLI, Snowpark Pandas and other Snowflake capabilities to streamline the overarching ML process.

Snowflake recently launched new capabilities to help organizations build data agents connected to enterprise data environment. This session explores why Snowflake makes it easy to iterate, monitor and observe agentic AI systems. Learn associated best practices related to RBAC integration in agentic workflows and applications. The session will also focus on change control and environment management and the software development lifecycle within the AI agents development lifecycle.

This session highlights Wipro's innovative approach to transforming financial operations using AI agents. By leveraging Wipro's deep industry expertise and Snowflake's data prowess, we have developed a scalable, secure, and intelligent system that revolutionizes the management of supplier-related queries around invoices and payments. Our solution has significantly increased processing efficiency, reduced latency and manual activities, and achieved high accuracy in responses. The implementation has led to substantial cost savings and improved response times, demonstrating the potential of AI-powered solutions in enhancing business operations.

FFT, a global leader in innovative manufacturing systems, has developed a solution to the persistent challenge of bridging IT and OT data. In just six months, FFT launched the FFT DataBridge, which resides on shopfloor edge devices and seamlessly integrates production data into the Snowflake AI Data Cloud. This solution unlocks critical shopfloor analytics, AI-based forecasting, and predictive maintenance. By leveraging the power of Snowflake, FFT is helping manufacturing companies transform their operations and is continuing their journey by building a suite of IT/OT-centric applications for the Snowflake Marketplace.

The retail and consumer goods industries are undergoing significant transformation, driven by shifting consumer behaviors, global economic changes, supply chain disruptions and, most importantly, rapid technological innovation. This session is designed for business and technology leaders in RCG, offering them insights and strategies needed to navigate and thrive in this evolving landscape. Learn from the transformational experience of the leading global consumer goods company, Snowflake industry experts and key partners as they explore how data and AI technologies are shaping the industries' future.

Connecting machines and structuring industrial data has long been one of the toughest challenges in smart manufacturing. Before unlocking the power of AI, large language models, or advanced analytics, companies must first solve the foundational task of harmonizing and organizing their data—without this, bad data only leads to bad AI.

This session covers the journey from building a Unified Namespace as the data foundation to scaling predictive use cases such as maintenance, quality optimization, and process improvements. Using customer stories from discrete and process manufacturing, we will show howDXC &Snowflake enables enterprises to connect IoT data at scale, establish a harmonized taxonomy across global operations, and drive measurable business outcomes.

By unifying diverse industrial IoT and enterprise data into a governed data layer, the Unified Namespace enables creation of an operational digital twin—a live, authoritative representation of manufacturing systems and assets that fuels scalable AI use cases like predictive maintenance, autonomous control, and AI-driven shop floor assistance. Attendees will learn howDXCs &Snowflake’s IoTbest-practicespower OT/IT convergence, continuous digital twin evolution, and AI-driven operational excellence.

Collecting and analyzing data is at the heart of every pharmaceutical R&D organization. As a result, we at Merck KGaA store large amounts of very diverse data – from assay results in early research, to operational data from clinical trials, human clinical trial data and data related to regulatory submissions. In the upcoming era of artificial intelligence (AI), making this data available to AI systems at scale is a strategic imperative. For this reason, we have formed a cross R&D workstream to modernize our compute & story ecosystem. In this presentation, we will explain the approach taken, the main challenges faced and how we are addressing them. One important component of our new ecosystem is Snowflake, where we leverage automation and blueprints to enable a consistent technical foundation across the different R&D domains.

RSG Group – the global fitness powerhouse behind Gold’s Gym, McFIT, and JOHN REED – modernized its fragmented, manual data infrastructure into a scalable, low-maintenance analytics platform using Snowflake, Fivetran, and Coalesce. With a lean team and growing data needs across 900+ studios in 30 countries, the company replaced brittle pipelines and slow onboarding with automated ingestion, governed transformations, and self-service analytics. In this session, Head of Data & Business Intelligence Christopher Rüge will share how RSG Group reduced data integration time from 80 hours to 30 minutes, established end-to-end lineage and GDPR compliance with Coalesce, enabled data-driven decisions, and a strong foundation for AI use cases like personalization, churn prediction, and operational insights.

At this session, Sascha Urban, VP of Data at Blinkist, will reveal how his team went from data chaos to driving measurable business impact. Learn the three mindset shifts that freed up 30% of engineering time and turned a cost center into a true revenue driver.

Bayer is redefining how business questions get answered—fast, smart, and at scale. Together with ThoughtSpot, this session will share how Bayer uses ThoughtSpot on Snowflake to move beyond static dashboards and transition towards agentic analytics. With natural language querying, real-time insights, and AI-powered recommendations, Bayer enables users globally to make informed, data-driven decisions. You’ll hear how Bayer rolled out ThoughtSpot across multiple teams, trained diverse user personas, and optimized for both performance and Snowflake credit consumption.

Join us on our journey as we set out to transform a vast archive of 35,000 reports into structured, actionable data. Guided by the power of Snowflake Data Cloud and Document AI, we trained intelligent models to extract and organize critical information. Our adventure concludes with a seamless interface, where business users can easily access and leverage these insights. Discover how our team’s innovative path turned complexity into clarity, unlocking new value for the organization.

Evgenii, platform engineer at a global pharmaceutical company invites you to explore the journey in building a cloud-native Federated Data Platform powered by dbt Cloud, Snowflake, and Data Mesh principles. Learn how we defined foundational tools and standards, and how we enabled automation and self-service to empower teams across the organization.

As Germany's largest insurance groups embrace AI transformation, the challenge isn't just implementing large language models—it's building scalable, compliant infrastructure for enterprise-grade AI workflows. This session explores how Inverso, as a specialized Snowflake MSP, is revolutionizing insurance operations by combining Snowflake's data platform with cutting-edge AI to create production-ready solutions for automated claims processing and policy interpretation.

In this talk, we present our Proof of Concept (PoC) for Cortex Analyst on Snowflake, enabling interactive queries on complex geospatial data enriched with sociodemographic, market, and infrastructure information. An AI-powered text-to-SQL interface translates natural language queries into SQL in real time, with results shown in tables and visualizations. All of this leverages Snowflake’s built-in security and governance features.

Rethink how you build open, connected, and governed data lakehouses: integrate any Iceberg REST compatible catalog to Snowflake to securely read from and write to any Iceberg table with Catalog Linked Databases. Unlock insights and AI from semi-structured data with support for VARIANT data types. And enjoy enterprise-grade security with Snowflake's managed service for Apache Polaris™, Snowflake Open Catalog.

Explore how Siemens is transforming data sharing with innovative data products, powered by Snowflake for seamless, automated, and cross-platform data sharing. This transformative approach empowers Siemens to enhance collaboration, and unlock the full potential of enterprise data, paving the way to becoming a truly data-driven organization. Join us to explore their journey and key insights.