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Most analytics today are reactive; they wait for someone to ask the right question or check the right dashboard. With Generative AI and Agentic Systems, we can flip this model: building assistants that are proactive, monitoring data signals, detecting anomalies, and pushing actionable insights to decision-makers without waiting for a prompt.

In this workshop, set in the context of an e-commerce company, you’ll learn how to design and implement a Proactive Insights Copilot using AWS services. The copilot combines knowledge grounding with specialized agents and event-driven triggers to deliver context-rich, timely insights that move teams beyond static dashboards.

The workshop is guided by AWS’s prescriptive guidance.

• Building Serverless Architectures for Agentic AI on AWS – scalable, event-driven architectures using Amazon Bedrock, EventBridge, and Lambda.
• Agentic AI Frameworks, Protocols, and Tools on AWS – guidance for choosing frameworks, integrating tools, and orchestrating multi-agent systems using protocols such as the Model Context Protocol (MCP).

By the end of the day, you’ll have hands-on experience building a copilot that anticipates needs, surfaces insights automatically, and operates with governance and trust, all demonstrated through an e-commerce lens but applicable across industries.

Who Should Attend

• Solutions Architects exploring Generative AI and agentic design patterns
• Developers & Engineers wanting hands-on experience building with AWS services
• Data & Analytics Leaders looking to extend BI capabilities with AI
• Business & Operations Stakeholders curious about how AI surfaces insights proactively

What You’ll Need

• Basic familiarity with AWS services (S3, Lambda, EventBridge, IAM)
• Comfort navigating the AWS Management Console
• Awareness of business KPIs (e.g., conversion, cart abandonment, Average Order Value)
• No advanced coding or ML expertise required

What Will Be Provided

• Access to a ready-to-use AWS environment for hands-on labs
• Sample e-commerce data for use cases and exercises
• Guided instructions and starter resources (Lambda functions, EventBridge rules, datasets)
• A reference guide and cleanup steps to continue learning post-workshop

12:30 – 1:10 | Introduction (40 min)

• Why dashboards and traditional BI miss critical signals
• Overview of Generative AI, AI Agents, and Agentic Systems
• Review Knowledge Grounding with Amazon Bedrock KB

1:10 – 3:10 | From Assistant to Agentic System (2 hrs)

• Move beyond Q&A to agents that plan and act
• Configure a Bedrock Agent with specialized tools: Sales KPI Checker Agent, Inventory Checker Agent, Refund Anomaly Detector Agent
• Demonstrate orchestration through an Advisor Agent, coordinating tools, and KB
• Hands-on build and testing with extra troubleshooting time
• Mini-governance touchpoints: least-privilege IAM roles, audit trails, tool contracts

3:10 – 3:50 | Making Insights Proactive (40 min)

• Use Amazon EventBridge to configure proactive triggers
• Scheduled triggers: weekly KPI briefing
• Event-driven triggers: cart abandonment > 50%, inventory thresholds
• Deliver insights via email
• Discuss scaling patterns for proactive insights

3:50 – 4:10 | Governance, Guardrails & Lifecycle (20 min)

• Why trust and explainability matter
• Guardrails: grounding, moderation, scoped permissions
• Governance (AgentOps): version control, pipelines, monitoring

4:10 – 4:30 | Wrap-Up & Q&A (20 min)

• Recap: BI dashboards → knowledge-grounded assistant → agentic system → proactive insights
• Participant reflections and discussion of use cases beyond e-commerce