Capstone Project: The Enterprise Architect's Masterpiece

Congratulations on reaching the end of the AWS Bedrock: End-to-End course. It is time to prove your mastery. You will build a complete, professional AI system that solves a real business problem using the full AWS Bedrock stack.

The Mission: "QuantumCorp Intelligence"

Your goal is to build an AI assistant for a fictional global energy company called QuantumCorp.

1. Requirements (The Full Stack)

Your solution must include:

A Foundation Brain: Use Claude 3.5 Sonnet (via Bedrock) as the primary reasoning engine.
Knowledge Base (RAG): Connect the agent to a folder of "QuantumCorp Policy" PDFs in S3.
Action Group (Tools): Build a Lambda-backed tool that can "Check Solar Panel Efficiency" based on an ID.
AgentCore Orchestration: Use a multi-node graph to ensure that "Efficiency Checks" are always verified against the "Policy Knowledge Base."
Security (Guardrails): Implement a Bedrock Guardrail to redact PII and block questions about "Fossil Fuels" (QuantumCorp is 100% green!).
Observability: Configure CloudWatch logging and build a basic dashboard mockup showing token spend.

The Architectural Blueprint

graph TD
    User[Human Query] --> G[Guardrail: Security Check]
    G --> AC[AgentCore Orchestration]
    AC --> KB[Knowledge Base: Policy Search]
    AC --> AG[Action Group: Panel Data API]
    AC --> Verify[AI Critic: Fact Check]
    Verify --> Out[Final Response]
    
    AC -.-> CW[CloudWatch: Permanent Logs]
    AC -.-> Budget[Budgets: Cost Alerts]

Deliverables Checklist

Infrastructure Diagram: A visual map of your S3, Lambda, KB, and Agent connections.
IAM Policies: The JSON for your Agent's Execution Role.
The OpenAPI Schema: Defining your Action Group (Solar Panel Tool).
The System Prompt: The detailed instructions for your Agent.
Trace Evidence: A screenshot or log snippet showing the agent's thought process solving a sample query.

Final Congratulations! 🚀

You are no longer an "AI Enthusiast." You are an AWS Bedrock Engineer. You have the skills to build, secure, and scale high-fidelity AI applications that work in the real world.

What's Next?

Join the Community: Share your Capstone project on LinkedIn or GitHub.
Get Certified: You are now prepared for the AWS Certified AI Practitioner and parts of the Machine Learning Specialty exams.
Launch: Go build something that changes how your company works!

The cloud is waiting. The brains are ready. Go create.

Capstone Project: Enterprise AI Assistant