AI Solution Architecture and Strategy

Based on your problem analysis, let's design the AI architecture and strategy for your solution.

1. **AI Model Selection**: 
   - What type of AI/ML models are most suitable for this problem?
   - Consider options like: LLMs, computer vision models, recommendation systems, classification models, etc.
   - Justify your choice based on the specific requirements

2. **System Architecture**:
   - Design the high-level architecture of your solution
   - Include key components: AI models, data pipelines, APIs, user interfaces
   - Define how these components interact
   - Consider deployment architecture (cloud, edge, hybrid)

3. **Data Strategy**:
   - What data will you need to train/fine-tune your models?
   - How will you collect, process, and store data?
   - Address data privacy and security considerations
   - Define your data pipeline architecture

4. **AI Agent Design** (if applicable):
   - Define the agent's capabilities and behaviors
   - Design the decision-making framework
   - Specify interaction patterns with users and other systems
   - Consider error handling and fallback mechanisms

5. **Integration Strategy**:
   - How will your solution integrate with existing systems?
   - Define APIs and interfaces
   - Consider authentication and authorization
   - Plan for monitoring and observability

Provide a detailed technical design that addresses each of these areas.