Enterprise AI is moving beyond simple chatbots into autonomous data agents, but orchestrating their interactions with massive, distributed databases introduces a critical flaw: the latency bottleneck. Traditional hub-and-spoke architectures rely on continuous network round-trips to centralized data warehouses. The network latency interrupts the agentic reasoning loop, turning sub-second thought processes into tasks that take minutes. What if the agent and the database lived inside the same immutable container?

Here we will explore the architecture of "Self-Contained Data Agents." By combining an agentic orchestration layer with an embedded OLAP engine (chDB) inside a single Docker container, we can eliminate network hops and achieve sub-second, direct-memory data access.
We will show how to seamlessly map this architecture to AWS, utilizing AWS Fargate for true scale-to-zero serverless compute, Amazon S3 for "fetch-on-boot" state persistence, and Amazon CloudWatch for observability.

AWS Community Day Bengaluru 2026