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.

Discover how Boehringer is managing data translation and harmonization enabling the creation of seamless data integrations worldwide. This session will detail how Boehringer transformed its fragmented, data landscape into a centralized data factory on Snowflake, reducing costs while dramatically improving scalability and efficiency. We will explore how leveraging Cortex LLM Functions automates data mapping and consistency, enabling the creation of integrated data products that empower global business steering. Join us to learn how to overcome data harmonization challenges and build a data factory mindset for better decision-making and unprecedented growth.

In this session, we’ll walk through why we decided to abandon Redshift, driven by the need for elasticity, cost efficiency, and faster iteration. We'll also discuss how we designed a structured migration blueprint, including a vendor evaluation, proof of concept, and a four-pillared framework to guide our journey.

We’ll then dive into the areas where things got turbulent: why off-the-shelf translation tools failed, why LLMs didn’t help, and the specific technical challenges we encountered. From surrogate key issues to Stitch's unflattened data and Snowplow’s monolithic event tables.

We’ll explain how we kept the migration on track by turning our analysts into co-navigators, embedding them into validation loops to leverage domain knowledge, and how a parallel ingestion strategy helped stabilize progress during high-risk phases.

Finally, we’ll share what this migration unlocked for us: faster ingestion, better permission management and more. Expect real-world pitfalls, lessons learned, and actionable insights for your own migration journey.

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.