ClaimAssist is a comprehensive web application designed to streamline the documentation and processing of insurance claims following property damage from wildfires. Created during the Cal State Fullerton Hackathon, the application focuses on providing a user-friendly, supportive interface to help victims organize and file insurance claims efficiently.
- Multi-step Guided Process: Step-by-step interface to guide users through the entire claim documentation process
- Room & Item Selection: Visual interface for selecting rooms and documenting items with photos and details
- Multi-language Support: Internationalization features for broader accessibility
- Currency Conversion: Support for documenting items purchased in 15+ foreign currencies
- Mobile-Responsive Design: Optimized for use on any device, especially important in emergency situations
- Price Estimation: AI assists users with estimating replacement costs for lost items
- Documentation Suggestions: Helps users locate documentation sources like email receipts or photo libraries
- Duplicate Detection: Identifies potential duplicate entries to prevent claim issues
- Multi-user Collaboration: Family members can work together across sessions to complete inventory
- Session Persistence: Saves work in progress to prevent data loss
- Customizable Templates: Various document formats for organizing inventory information
- PDF Generation: Create professional-quality printable claim documents
- Export Options: With or without photos, detailed or summary views
- React + TypeScript: For a robust, type-safe UI
- TanStack Query: For efficient data fetching and caching
- Tailwind CSS + Shadcn UI: For responsive, beautiful design
- HTML2PDF.js: For client-side PDF generation
- Node.js + Express: For a lightweight, efficient server
- PostgreSQL + Drizzle ORM: For data persistence and schema management
- OpenAI API: For AI-powered assistance features
ClaimAssist was developed by a team of Computer Science students from Cal State Fullerton:
- Duy Le: Junior in CS, interested in AI and fintech
- Jacob Fishel: Junior in CS, interested in AI and machine learning
- Philip Ma: 3rd year CS student, interested in Fintech
- Bryan Orozco: Sophomore in CS, interested in working with large scale data and game development
- Node.js v18+
- PostgreSQL database
- OpenAI API key
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Clone the repository:
git clone https://github.com/yourusername/claimassist.git cd claimassist -
Install dependencies:
npm install
-
Set up environment variables: Create a
.envfile with the following variables:DATABASE_URL=postgresql://username:password@localhost:5432/claimassist OPENAI_API_KEY=your_openai_api_key -
Initialize the database:
npm run db:push
-
Start the development server:
npm run dev
- Personal Information: Enter your contact information and policy details
- Room Selection: Select rooms affected by the wildfire
- Item Documentation: For each room, document lost or damaged items:
- Take or upload photos
- Provide details (name, description, estimated value)
- Utilize AI assistance for price estimates when needed
- Use currency converter for items purchased abroad
- Review & Templates: Review your documented items and select a template format
- Generate PDF: Create a professional PDF document to submit to your insurance company
The application helps users organize documentation from various sources:
- Purchase history from retailers (Amazon, Walmart, etc.)
- Email receipt searches
- Photo libraries (Google Photos, Apple Photos, etc.)
- Credit card statements
Contributions are welcome! Please feel free to submit a Pull Request.
- Fork the repository
- Create your feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add some amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
This project is licensed under the MIT License - see the LICENSE file for details.
- Cal State Fullerton Hackathon for the opportunity to develop this project
- Victims of wildfires who inspired us to create a tool that could help in the recovery process