S-1 Analysis AI

A sophisticated AI-powered tool for analyzing S-1 IPO filings using Google's Gemini AI. This application provides comprehensive financial analysis, data extraction, and interactive Q&A capabilities for SEC S-1 documents.

📸 Screenshots

Financial Analysis Dashboard

Comprehensive financial health scoring, waterfall charts, and detailed ratio analysis

Application Interface

Clean, modern interface with sidebar navigation and multiple analysis tools

🚀 Features

📊 Summary & Q/A

Interactive Analysis: Ask specific questions about the S-1 filing
Predefined Questions: Quick access to common queries like risk factors, business model, and key executives
Confidence Scoring: AI-generated confidence scores for each analysis
Citation Support: Direct quotes from the document to support answers

📈 Data Extraction

Financial Metrics Extraction: Extract key financial data points with automatic parsing
Visual Charts: Automatic chart generation for numeric data with 2+ data points
Predefined Extractions: One-click extraction for common metrics like revenue, net income, and operating expenses
Period-based Analysis: Track financial metrics across different time periods

💰 Financial Analysis

Comprehensive Financial Health Score: 0-100 scoring system with detailed ratings
Waterfall Charts: Visual representation of financial flows and changes
Financial Ratios: Automated calculation and analysis of:
- Profitability ratios
- Growth and efficiency metrics
- Liquidity and leverage ratios
Trend Analysis: Year-over-year change analysis with AI commentary
Hidden Insights: AI-powered discovery of significant but buried financial information
IPO-Specific Analysis: Specialized insights on use of proceeds, customer concentration, and share structure

💬 Interactive Chat

Document-aware conversations: Chat with the AI about the specific S-1 filing
Contextual responses: AI maintains context throughout the conversation
Streaming responses: Real-time response generation for better user experience

🛠 Technical Stack

Frontend: React 19 with TypeScript
AI Integration: Google Gemini AI (@google/genai)
Visualization: Chart.js for interactive charts and graphs
Styling: Tailwind CSS with custom dark theme
Markdown Support: Enhanced markdown rendering with math support (KaTeX)
Build Tool: Vite for fast development and optimized builds

📋 Prerequisites

Node.js (version 16 or higher)
Google Gemini API Key - Get one from Google AI Studio

🚀 Getting Started

1. Clone the Repository

git clone https://github.com/raztronaut/S-1-Analysis-AI.git
cd S-1-Analysis-AI

2. Install Dependencies

npm install

3. Configure Environment Variables

Create a .env.local file in the root directory:

GEMINI_API_KEY=your_gemini_api_key_here

4. Run the Application

npm run dev

The application will be available at http://localhost:5173

📖 How to Use

1. Upload Document

Start by uploading an S-1 filing document
Supported formats: PDF, TXT, and other text-based documents
The app will process and prepare the document for analysis

2. Navigate Between Features

Use the sidebar to switch between different analysis modes:

Summary & Q/A: Ask questions or use predefined queries
Data Extraction: Extract specific financial metrics and visualize trends
Financial Analysis: Get comprehensive financial health assessment
Chat: Have a conversation about the document

3. Analyze Results

Review AI-generated insights with confidence scores
Click on citations to see exact quotes from the document
Download or export analysis results for further use

🎯 Use Cases

Investment Analysis: Evaluate IPO opportunities with AI-powered insights
Due Diligence: Quickly extract and analyze key financial metrics
Research: Academic or professional research on public company filings
Educational: Learn about financial analysis and S-1 document structure

🏗 Project Structure

src/
├── components/           # React components
│   ├── common/          # Reusable UI components
│   ├── Chat.tsx         # Interactive chat interface
│   ├── DataExtraction.tsx # Financial data extraction
│   ├── FinancialAnalysis.tsx # Comprehensive financial analysis
│   ├── FileUpload.tsx   # Document upload handling
│   ├── Sidebar.tsx      # Navigation sidebar
│   └── SummaryQA.tsx    # Q&A interface
├── services/            # External service integrations
│   └── geminiService.ts # Google Gemini AI integration
├── data/               # Sample data and constants
├── types.ts            # TypeScript type definitions
├── constants.ts        # Application constants
└── App.tsx             # Main application component

🔧 Configuration

Environment Variables

GEMINI_API_KEY: Your Google Gemini API key (required)

Customization

Modify constants.ts to add custom predefined questions and extractions
Update the theme in the CSS for custom styling
Add new analysis features by extending the component structure

🚀 Building for Production

npm run build

The built application will be in the dist/ directory, ready for deployment to any static hosting service.

📝 API Integration & AI Architecture

Core AI Engine

The application is powered by Google Gemini 2.5 Pro, leveraging advanced large language model capabilities for sophisticated financial document analysis. All AI interactions are handled through the @google/genai library with structured prompting and response parsing.

Multi-Specialist AI Architecture

The application employs a unique multi-agent approach for comprehensive financial analysis:

🎯 Specialized AI Analysts

Profitability Analyst: Calculates margins, gross profit ratios, and profitability metrics
Growth Metrics Analyst: Analyzes revenue growth, retention rates, and expansion metrics
Balance Sheet Analyst: Evaluates liquidity ratios, debt-to-equity, and financial stability
Trends Analyst: Performs year-over-year comparative analysis across key metrics
Risk & Strategy Analyst: Identifies competitive advantages, dependencies, and regulatory risks
Investigative Analyst: Discovers hidden financial commitments and off-balance-sheet obligations
IPO Specialist: Analyzes use of proceeds, customer concentration, and share structures
Cash Flow Analyst: Evaluates burn rates, runway, and cash management

🔄 Synthesis Process

A lead AI analyst combines insights from all specialists, cross-references findings against the original document, and generates a holistic financial health assessment.

AI-Powered Features

📊 Summary & Q/A (`analyzeQuery`)

Dual-Analyst Approach: Risk assessor + growth strategist personas for balanced analysis
Confidence Scoring: 0.0-1.0 confidence metrics based on source material clarity
Citation Grounding: Every claim backed by verbatim document quotes
Temperature: 0.1 for focused, factual responses

📈 Data Extraction (`extractData`)

Chain-of-Thought Processing: Systematic document scanning with step-by-step verification
Structured Output: JSON responses with figures, periods, numeric values, and units
Precision Mode: Temperature 0.0 for maximum accuracy in financial data extraction
Multi-Format Support: Handles percentages, dollar amounts, and various financial metrics

💬 Interactive Chat (`startChat` & streaming)

Contextual Memory: Maintains conversation history and document awareness
Real-Time Streaming: Progressive response generation for immediate feedback
Rich Formatting: Supports markdown, LaTeX formulas, tables, and citation tooltips
Adaptive Temperature: 0.2 for natural conversation while maintaining accuracy

💰 Financial Analysis (`performFinancialAnalysis`)

Parallel Processing: Multiple AI specialists analyze simultaneously for efficiency
Comprehensive Scoring: 0-100 financial health score with detailed justification
Visual Data Generation: Creates waterfall chart data and visualization metrics
Cross-Validation: Lead analyst verifies specialist findings against source document

AI Response Processing

JSON Parsing: Robust handling of AI responses with fallback error handling
Citation Extraction: Automatic parsing and formatting of document references
Streaming Support: Real-time response chunks for improved user experience
Error Recovery: Graceful handling of malformed AI responses with user feedback

Prompt Engineering Strategies

System Instructions: Detailed role-based prompts for each AI specialist
Response Formatting: Structured JSON schemas for consistent output parsing
Citation Requirements: Mandatory verbatim quotes for all factual claims
Temperature Control: Optimized settings per use case (0.0 for data, 0.2 for chat)
Context Management: Efficient document chunking and context window optimization

🤝 Contributing

Fork the repository
Create a feature branch (git checkout -b feature/amazing-feature)
Commit your changes (git commit -m 'Add amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request

📄 License

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

🙏 Acknowledgments

Google Gemini AI for powerful language model capabilities
Chart.js for beautiful data visualizations
React Team for the excellent framework
Vite for lightning-fast development experience

📞 Support

For questions, issues, or feature requests, please open an issue on GitHub or contact the maintainer.

Built with ❤️ for better financial analysis and AI-powered insights

Name		Name	Last commit message	Last commit date
Latest commit History 5 Commits
components		components
data		data
docs/images		docs/images
services		services
.gitignore		.gitignore
App.tsx		App.tsx
README.md		README.md
constants.ts		constants.ts
index.html		index.html
index.tsx		index.tsx
metadata.json		metadata.json
package.json		package.json
tsconfig.json		tsconfig.json
types.ts		types.ts
vite.config.ts		vite.config.ts

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