An intelligent system for analyzing enterprise AI case studies using the Claude 3.5 Sonnet API. The system supports two main modes of operation:

1. Analyzing case studies from provided URLs in a CSV file.
2. Discovering and analyzing case studies from company websites using the Firecrawl API.

• CSV Mode: Analyze specific case study URLs provided in a CSV file.
• Website Mode: Automatically discover and analyze case studies from company websites using Firecrawl's map endpoint.
• Intelligent case study identification powered by Claude 3.5 Sonnet.
• Content extraction handled by Firecrawl's scrape endpoint.

• Content Extraction (via Firecrawl API):
  • Map endpoint (/v1/map): Discovers links on the website.
  • Scrape endpoint (/v1/scrape): Extracts content in markdown format and retrieves metadata for context.
• Case Study Identification:
  • Uses Claude to identify potential case study links.
  • Filters content to ensure only relevant case studies are processed.
• Content Analysis:
  • Checks for enterprise AI qualification.
  • Performs a detailed, multi-section analysis.
  • Assesses business impact and technology stack.

The system creates three types of reports:

• Executive Summary
• AI Strategy Analysis
• Technical Implementation Details
• Business Impact Assessment
• Key Success Factors
• Lessons Learned

• Patterns across multiple implementations.
• Common success factors.
• Technology trends.
• ROI metrics and implementation challenges.

• Company profiles
• Technology stacks
• Success metrics and implementation scales
• Overall trends in enterprise AI adoption

• Map Endpoint (/v1/map):

  map_result = app.map_url(website_url, params={'includeSubdomains': True})

  Used for discovering all links on a website.

• Scrape Endpoint (/v1/scrape):

  params = {
      "url": url,
      "onlyMainContent": True,
      "formats": ["markdown"],
      "timeout": 30000
  }

  Used for content extraction from specific pages.

• Link Analysis: Identifies relevant case study URLs.
• Content Analysis: Checks for enterprise AI relevance.
• Report Generation: Produces comprehensive, structured analysis reports.

Input (CSV/Website) → Firecrawl Map → Link Analysis → Content Extraction → Claude Analysis → Report Generation

project/
├── src/
│   ├── scrapers/
│   │   ├── website_crawler.py  # Firecrawl map integration
│   │   └── web_loader.py       # Firecrawl scrape integration
│   ├── processors/
│   │   └── claude_processor.py # Claude API integration
│   ├── config.py               # Configuration settings
│   └── main.py                 # Main application logic
├── input/                      # Input CSV files
├── raw_content/                # Extracted raw content
│   └── case_[id]/
│       ├── raw_content.txt
│       ├── structured_content.json
│       └── metadata.json
├── reports/
│   ├── individual/             # Individual reports
│   ├── cross_case_analysis/    # Cross-case analysis
│   └── executive_dashboard/    # Executive dashboard
└── logs/                       # Processing logs

1. Clone the repository:

   git clone https://github.com/yourusername/ai-case-study-analyzer.git
   cd ai-case-study-analyzer

2. Create a virtual environment:

   python -m venv .venv
   source .venv/bin/activate  # On Windows: .venv\Scripts\activate

3. Install dependencies:

   pip install -r requirements.txt

4. Set up environment variables in .env:

   ANTHROPIC_API_KEY=your_claude_api_key
   FIRECRAWL_API_KEY=your_firecrawl_api_key
   

• Place your CSV file in the input/ directory with a column named url containing case study URLs.

• Provide a company website URL to:
  1. Map all website links using Firecrawl.
  2. Identify and analyze case study content using Claude.
  3. Extract content and generate comprehensive reports.

Run the analyzer:

python -m src.main

1. Map Endpoint:

   • Discovers all links on a website.
   • Parameters: includeSubdomains: true, ignoreSitemap: false, limit: 5000.

2. Scrape Endpoint:

   • Extracts main content from individual pages.
   • Parameters: onlyMainContent: true, formats: ["markdown"], timeout: 30000.

1. Link Analysis:

   • Model: claude-3-5-sonnet-20241022.
   • Temperature: 0.2.
   • Max tokens: 4096.

2. Content Analysis:

   • Checks for enterprise AI qualification.
   • Performs multi-section analysis and report generation.

# Enterprise AI Implementation Report: [Company Name]
1. **Executive Summary**
   [Summary of implementation and outcomes]

2. **AI Strategy Analysis**
   [Detailed analysis of AI strategy]

{
  "case_1": {
    "company": {...},
    "technologies": [...],
    "success_factors": {...},
    "business_impact": {...}
  }
}

Contributions are welcome!

This project is licensed under the MIT License.