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Nontech VC - Data-Driven Investment Analysis Platform

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This project was built as part of the Data-Driven VC Hackathon organized by Red River West & Bivwak! by BNP Paribas

Description

A modern web application that performs comprehensive analysis of tech companies using multiple data sources to provide investment insights.

Features

  • Real-time Company Analysis: Analyze any tech company using just their domain name

  • Multi-factor Assessment: 14-step analysis covering:

    • Competitor Analysis
    • GitHub Repository Analysis
    • Code Quality Assessment
    • Founder Background Analysis
    • Key People Assessment
    • Market Analysis
    • Financial Assessment
    • Team Composition
    • Technology Stack
    • Growth Metrics
    • Risk Assessment
    • Market Sentiment
    • Competitive Position
    • Final Scoring
  • Interactive UI:

    • Dark/Light mode support
    • Real-time progress tracking
    • Expandable detailed analysis for each step
    • AI-powered explanations
    • Visual performance indicators
    • Markdown support for rich text formatting

Tech Stack

Frontend

  • React with TypeScript
  • Material-UI (MUI) for components
  • React-Markdown for content rendering
  • KaTeX for mathematical formulas

Backend

  • FastAPI (Python)
  • Async processing for real-time updates
  • Integration with multiple data providers:
    • Harmonic.ai for company data
    • GitHub API for repository analysis
    • OpenAI API for intelligent summaries

Setup

  1. Clone the repository:
git clone https://github.com/yourusername/data-driven-vc.git
cd data-driven-vc
  1. Set up environment variables: Based on .env.template create a .env file in the root directory

  2. Install backend dependencies:

cd backend
pip install -r requirements.txt
  1. Install frontend dependencies:
cd frontend
npm install
  1. Start the backend server:
cd backend
uvicorn main:app --reload
  1. Start the frontend development server:
cd frontend
npm run dev

Usage

  1. Open the application in your browser
  2. Enter a company's domain name in the search field
  3. Click "Analyze" to start the assessment
  4. Watch as each analysis step completes in real-time
  5. Expand any step to view detailed information
  6. Use the "Explain this to me" button for AI-generated summaries
  7. Toggle dark/light mode as needed

API Endpoints

  • POST /analyze-domain: Start a new analysis
  • GET /job/{job_id}: Get analysis status and results
  • POST /summarize-step: Get AI explanation for a step

TODO

  • Add missing technologies list

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Commit your changes
  4. Push to the branch
  5. Create a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

  • Harmonic.ai for company data
  • OpenAI for AI capabilities
  • Material-UI for the component library
  • All other open-source libraries used in this project

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Repository for team 6 - Startup Analysis

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