Putting It All Together

This is where all your hard work pays off! We're going to combine everything you've learned to create a complete, production-ready AI System for Cozy Café. This system will handle real business operations and demonstrate the true power of AI Systems.

By the end of this module, you'll have:

• A complete AI System with multiple components working together
• A workflow engine orchestrating tasks
• Multiple MCP servers for different functions
• An intelligent agent managing everything
• A real business solution you can adapt for any use case

Let's see how all our components work together to create a powerful business solution:

System Capabilities

Our complete system will:

1. Customer Service - Handle inquiries 24/7
2. Feedback Management - Collect and analyze customer feedback
3. Menu Information - Answer questions about offerings
4. Business Analytics - Provide insights and trends
5. Task Automation - Handle routine operations
6. Proactive Alerts - Notify about important issues

Let's create a workflow engine to orchestrate our AI System:

Let's add a Menu MCP server to handle menu-related queries:

Now let's create an integrated system that uses all our components intelligently:

Let's add the final touches to make your system ready for real-world use:

Let's see our complete system in action with a realistic business day:

<Quiz questions={[ { question: "What is the main purpose of a workflow engine in our AI System?", options: [ "To store data in databases", "To orchestrate tasks and manage dependencies between them", "To create user interfaces", "To send emails" ], correctAnswer: 1, explanation: "The workflow engine orchestrates tasks, manages dependencies, and ensures operations happen in the correct order - like a conductor directing an orchestra." }, { question: "How do multiple MCP servers work together in our system?", options: [ "They compete for resources", "Each handles specific domain functionality and the AI agent coordinates between them", "They all do the same thing for redundancy", "They can't work together" ], correctAnswer: 1, explanation: "Multiple MCP servers each handle specific domains (feedback, menu, analytics) and the AI agent intelligently coordinates between them based on user needs." }, { question: "What makes our business logic 'intelligent'?", options: [ "It uses many if-else statements", "It runs very fast", "It applies context-aware rules and learns from patterns", "It has a large database" ], correctAnswer: 2, explanation: "Intelligent business logic applies context-aware rules (like alerting on low ratings), learns from patterns, and makes decisions based on multiple factors." }, { question: "What's the benefit of containerizing our AI System with Docker?", options: [ "It makes the code run faster", "It ensures consistent deployment across different environments", "It reduces the code size", "It eliminates the need for MCP servers" ], correctAnswer: 1, explanation: "Docker containerization ensures our AI System runs consistently across different environments (development, staging, production) with all dependencies properly configured." } ]} />