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AI Enterprise Case Study Analyzer

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.
Screenshot 2024-11-05 at 4 58 41 AM Screenshot 2024-11-05 at 4 58 49 AM Screenshot 2024-11-05 at 4 58 49 AM Screenshot 2024-11-05 at 5 03 37 AM

Core Features

1. Case Study Discovery & Analysis

  • 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.

2. Content Processing Pipeline

  • 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.

3. Report Generation

The system creates three types of reports:

a. Individual Case Study Reports (reports/individual/)

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

b. Cross-Case Analysis (reports/cross_case_analysis/)

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

c. Executive Dashboard (reports/executive_dashboard/)

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

Technical Architecture

1. Firecrawl Integration

  • 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.

2. Claude 3.5 Sonnet Integration

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

3. Data Processing Workflow

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

Project Structure

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

Installation & Setup

  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
    

Usage

1. CSV Analysis Mode

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

2. Website Analysis Mode

  • 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

API Integration Details

Firecrawl API

  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.

Claude 3.5 Sonnet API

  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.

Output Examples

Individual Case Study Report

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

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

Cross-Case Analysis

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

Star History

Star History Chart

Contributing

Contributions are welcome!

License

This project is licensed under the MIT License.