Snowflake World Tour
Virtual

Token costs fell 80% last year. AI budgets still went up. Something is broken, and it isn’t the price of tokens.

This session reframes how enterprise teams should think about AI economics. “”Tokenomics””,  the obsession with per-token pricing, is the wrong unit of measure. The right metric is cost per correct outcome: what did the AI actually deliver, and what did it cost in total compute, human validation, and rework?

We’ll show why Snowflake’s architecture — data, context, and compute in one governed platform — produces a structural advantage in cost-per-outcome, not just token efficiency. We’ll use real benchmark data (47% → 86% task accuracy) and production deployment evidence to show how Cortex Code closes the gap between AI spend and business value. And we’ll walk through a practical governance framework — tagging, attribution, and budget controls — so AI cost is accountable, not opaque.

You’ll leave with a new metric, a governance blueprint, and the evidence to justify AI investment to your CFO.

In today’s fast-evolving digital landscape, scaling AI and data innovation is no longer optional—it’s essential to staying competitive. This session explores how forward-thinking organizations are transforming their business models by embedding AI and data at the core. Discover how to move from experimentation to enterprise-scale impact, unlock operational efficiencies, and drive customer-centric innovation. Learn from real-world examples, emerging trends, and actionable strategies to harness data and AI for smarter decision-making, improved performance, and long-term resilience.

Whether you are modernizing existing systems or building entirely new capabilities, this session will offer a strategic roadmap to shape tomorrow’s business—today.

Discover what’s new in Snowflake CoWork, the enterprise intelligence agent. Learn to move beyond dashboards to uncover the critical ‘why’ grounded in governed data. See how Snowflake CoWork and Cortex Agents enable natural language intelligence and actionable workflows.

Snowflake is redefining observability with Observe by Snowflake, a lakehouse-native observability platform. Learn how organizations can scale cost-effectively to hundreds of terabytes of telemetry per day and share data across business and operational contexts using Apache Iceberg on a telemetry lakehouse foundation. We will demo AI SRE, an AI agent that accelerates enterprise reliability workflows, and show how teams can engage with it through the Observe UI or coding agents to boost engineering productivity.

Learn how the SAP and Snowflake partnership is fueling advanced analytics and AI/ML on a unified enterprise data foundation—bringing together SAP and non-SAP data in the Snowflake AI Data Cloud with zero-copy, preserving governance, interoperability and semantics. See how SAP Business Data Cloud (BDC) data products can be enriched with enterprise and third-party data in Snowflake to unlock intelligent analytics and enterprise AI at scale.

Discover how Snowflake ML’s latest agentic capabilities accelerate your ML team’s productivity. Explore new features and see a live demo of Snowflake ML innovations.

When intelligence meets enterprise-grade orchestration. See how to build a production-ready multi-agent supply chain orchestrator that combines Snowflake Cortex AI’s deep data intelligence with Amazon Bedrock AgentCore’s enterprise-grade security and dynamic scaling to deliver unified analytics through a single conversational interface. By using the Model Context Protocol (MCP) as the open standard connecting both ecosystems, we’ll demonstrate how Snowflake Cortex Agent (with Cortex Analyst for text-to-SQL and Cortex Search for semantic retrieval) integrates with Bedrock AgentCore—which provides the secure, scalable runtime to orchestrate agents in production.

Discover SnowConvert AI’s capabilities for intelligent migration automation. Learn about semantic SQL translation using AST and Cortex AI, AI-driven issue resolution, automated data validation, ETL conversion to dbt on Snowflake, and ecosystem repointing for tools like Power BI.

Discover how Snowflake’s connectivity offerings act as the connective tissue for your data estate. Learn about the new Datastream service, Snowpipe Streaming, zero-copy integration, Openflow, and file processing, all accelerated with Snowflake CoCo.

Agentic AI can turn data into action, but only if it can find the right data and understand it. That’s a challenge since most enterprise data isn‚Äôt sufficiently self-describing. In this session, we‚Äôll define what AI-ready data looks like and show how Horizon Catalog provides the critical context layer that helps AI know your data. Horizon Catalog delivers quality-aware context directly to AI agents ‚Äî so they don‚Äôt just access data, they understand it. It also catalogs data from external systems, captures end-to-end lineage and usage patterns, and automates documentation and semantic modeling. Join us to see how a strong metadata foundation enables AI that‚Äôs more accurate and trustworthy.

Discover how Snowflake Interactive delivers 10x higher concurrency and 15x lower ingestion latency. Learn ideal business use cases for Snowflake Interactive, get a technical overview and deep dive, and see a live demo.

Discover how Snowflake Horizon Catalog solves Apache Iceberg governance and interoperability challenges. Learn about Polaris integration for an open ecosystem, Iceberg REST Catalog with secure cross-engine read/write access, and fine-grained row and column policies enforced on external engines like

Discover how Snowflake unifies transactional and analytical data in a single high-performance platform. Learn about Snowflake Postgres and Unistore breakthroughs that let you build responsive, real-time apps and AI experiences without complex ETL.

Discover Snowflake Datastream, a Kafka-compatible streaming service for AI apps. Learn how it integrates with Snowpipe Streaming and Dynamic Tables for end-to-end real-time pipelines. Build continuous AI and streaming apps with dramatically less operational overhead.

Discover Snowflake’s new cost governance capabilities. Learn how to track, analyze, and control your Snowflake spend effectively.

Discover Snowflake’s MCP server capabilities. Learn server setup, secure authentication, tool integration, and external client connectivity. Gain practical guidance and best practices for seamless MCP implementation.

Are you a new administrator tasked with managing a Snowflake environment — and feeling a little overwhelmed? You are not alone. This Hands-on Lab is built specifically for new admins who need to confidently set up, secure, and run their organization’s Snowflake environment from day one. It leverages Snowflake Blueprints (powered by the Blueprint Manager and CoCo) to establish an expert-vetted environment setup in hours rather than weeks. Join Snowflake’s Account Engineering team for a practical, guided tour of the platform’s most critical administrative capabilities. You’ll follow along in a live environment, so you leave with skills you can apply immediately, not just slides.

Use data engineering frameworks within the Snowflake Data Cloud to make your data ready for consumption, transform & deliver your data, and build & maintain pipelines.

Learn different ways of how to load data and choose the ingestion method that works best for you. Familiarize yourself with how to insert data from files, load data from a stream, create a Snowpipe and transform your data.

Learners will build a complete, AI-powered agent that can understand and act on your data. By utilising Snowflake’s latest AI SQL functions, Cortex Search/Analyst, and Snowflake CoWork, learners will develop practical skills to build and deploy end-to-end, AI-powered analytical applications, all within your Snowflake environment.

In this hands-on lab, you’ll build a full RAG application backed by Cortex Search by ingesting documents, chunking text, indexing with hybrid semantic search, and generating grounded answers using a model. They then apply Text-to-SQL to translate plain-English business questions into executable Snowflake queries, before evaluating their application using an LLM-as-judge framework that scores response quality across groundedness, context relevance, and answer relevance.