Nidhi Gupta

In a world where AI adoption is accelerating, your data architecture determines whether you lead or lag. Traditional data lakes and warehouses create silos that slow decisions, duplicate costs and block AI agents from accessing unified data. This session shows how to build an open, secure data lakehouse with Apache Iceberg in Amazon SageMaker. Learn how to query Iceberg tables in SageMaker directly from Snowflake, access Snowflake Horizon Catalog data through AWS Glue Data Catalog federation, and empower LLMs and AI agents to interact with your data estate. Walk away with architectural patterns that accelerate time to insights.

AI agents are no longer a research experiment. They are running in production, closing support tickets, managing data pipelines and making decisions at enterprise scale. This session shows you how to architect, deploy and operate production-grade AI agents on AWS, from a single agent to complex multiagent systems. Using Amazon Bedrock AgentCore, walk through real-world design patterns covering secure serverless deployment, tool and API integration via MCP, persistent memory, identity and access management, and end-to-end observability. See how AgentCore Gateway integrates with a Snowflake managed MCP server to orchestrate specialized subagents across your enterprise data ecosystem.

ISVs need to innovate quickly by building customizable AI agents for their customers. While open-source frameworks like LangGraph, CrewAI, and Strands Agents provide powerful capabilities, implementing enterprise-grade features like multi-tenant authentication, observability, and memory management remains challenging.

Discover how to effectively utilize Amazon S3 Tables in conjunction with Snowflake to streamline your data analytics workflow. In this session, topics will focus on the practical integration of Amazon S3 Tables and Snowflake, demonstrating how to unlock new possibilities in your approach to data management. Learn how to create a more efficient and flexible data environment that leverages the strengths of both Amazon S3 and Snowflake. Whether you're a data engineer, analyst or architect, this session will provide valuable insights to enhance your cross-platform data strategy and maximize the potential of your cloud data infrastructure.