Curious how AI can query your enterprise data without moving it or making things up? AWS and Teradata break down a trustworthy analyst agent built for real production use.

Topics Include:

• Neha Wadhera (AWS) introduces Trinath Yarlagadda and the Teradata Analyst Agent
• Enterprise AI data prep is costly, stalling most orgs at experimentation
• Agent answers plain-English questions via traceable SQL, zero data movement
• Barrier removal drives 3.7x ROI and 40% productivity gains
• Healthcare demo setup: hospital COPD readmissions, ~$10K cost per incident
• Four design principles: traceability, no data movement, deterministic-first, governance as code
• Main orchestrator agent plans, writes SQL, calls Teradata MCP server
• Complex questions escalate to a context-isolated data scientist agent
• Built on Claude Agent SDK, running Bedrock Claude Sonnet/Haiku/Opus
• Live demo: COPD readmission rates explored through iterative agent reasoning
• Delegation demo: data scientist agent runs in-database analysis, surfaces factors
• Pre/post tool hooks log every step and cost to CloudWatch
• Agent hosted on Amazon Bedrock AgentCore, fully serverless and scalable
• AgentCore delivers runtime, memory, identity, and observability out of the box
• Lessons learned: guardrails first, deterministic ops, multi-agent registry, ongoing evaluation

Participants:

• Trinath Yarlagadda – Principal Solution Architect – Agentic AI, Teradata
• Neha Wadhera – Sr Solutions Architect, Amazon Web Services  

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/