"AI investment advisor that gives personalized advice based on your actual stock portfolio."

NexusFolio is an AI-powered investment platform that provides personalized financial advice based on your actual stock portfolio. Using advanced RAG (Retrieval-Augmented Generation) technology, it analyzes your holdings, performs semantic search on market data, and delivers contextual investment insights with automated research reports and interactive visualizations.

• 🤖 Personalized AI Advisor: Chat with an AI that understands your specific portfolio composition
• 📊 Real-time Portfolio Tracking: Monitor your stocks with live market data and performance metrics
• 🔍 Automated Stock Research: Generate comprehensive analysis reports for each holding
• 📈 Interactive Visualizations: Dynamic charts showing portfolio performance and sector allocation
• 🎯 Contextual Recommendations: Get investment advice tailored to your actual holdings
• 🔐 Secure Authentication: Protected user data with enterprise-grade security

• Next.js 14 with TypeScript for full-stack application
• MongoDB Atlas with Mongoose ODM for user portfolio storage
• Auth0 for secure user authentication and session management
• Google Gemini 2.0 Flash Lite for AI-powered responses
• Vector Database for semantic search capabilities

• Custom RAG Service that integrates user portfolios with AI responses
• Semantic Search Service for contextual market data retrieval
• Portfolio Service for dynamic stock management and analysis
• Real-time API Endpoints for chat, portfolio, and stock operations

• React Components for portfolio visualization and management
• Interactive Stock Search with real-time data integration
• AI Chat Interface with personalized responses
• Responsive Design with modern UI components

• Portfolio Integration: AI analyzes your actual stock holdings
• Automated Research: Generate detailed stock analysis reports
• Node Chart Maker: Create interactive portfolio visualizations
• Real-time Data: Live stock prices and market information
• Personalized Advice: Contextual recommendations based on your holdings

• Data Integration: Connecting user-specific portfolio data with generic market information
• RAG Performance: Optimizing retrieval-augmented generation for personalized responses
• Real-time Updates: Managing live stock data with portfolio synchronization
• Vector Embeddings: Implementing semantic search for financial data

• API Rate Limits: Managing Google Gemini API usage and response times
• Database Optimization: Ensuring fast queries for portfolio operations
• Error Handling: Robust error management for financial data
• User Experience: Creating intuitive interfaces for complex financial concepts

• Personalized AI Integration: Successfully created a RAG system that provides investment advice based on actual user portfolios
• Real-time Data Pipeline: Built a robust system that fetches and processes live stock data
• User Experience: Created an intuitive interface for portfolio management and AI interaction
• Scalable Architecture: Designed a system that can handle multiple users with personalized data
• Security Implementation: Secure authentication and data protection for financial information
• Automated Research: AI-generated comprehensive stock analysis reports
• Interactive Visualizations: Dynamic charts and graphs for portfolio insights

• RAG Technology: Deep understanding of retrieval-augmented generation with user-specific data
• Financial Data Integration: Working with real-time stock APIs and portfolio management
• User Experience in FinTech: Importance of trust and transparency in financial applications
• AI Personalization: Making AI responses truly personalized rather than generic
• Full-stack Development: Integration of frontend, backend, database, and AI services
• Vector Databases: Implementing semantic search for contextual financial insights

• Enhanced portfolio analytics with advanced metrics
• Integration with more stock exchanges and markets
• Improved AI response accuracy with fine-tuned models
• Mobile app development for iOS and Android

• Advanced risk assessment and portfolio optimization
• Integration with brokerage accounts for automated trading
• Social features for sharing investment insights
• Multi-language support for global users

• Become the go-to AI investment advisor for retail investors
• Expand to cryptocurrency and alternative investments
• Develop institutional-grade analytics for professional traders
• Create an ecosystem of financial tools and services

• Next.js 14 - Full-stack React framework
• TypeScript - Type-safe JavaScript
• Tailwind CSS - Utility-first CSS framework
• React Components - Modular UI components

• Next.js API Routes - Serverless backend
• MongoDB Atlas - Cloud database
• Mongoose ODM - Object document mapping
• Auth0 - Authentication service

• Google Gemini 2.0 Flash Lite - Generative AI
• Vector Database - Semantic search
• RAG Architecture - Retrieval-augmented generation
• Real-time APIs - Live market data

• Git - Version control
• pnpm - Package manager
• ESLint - Code linting
• TypeScript - Type checking

• Node.js 18+
• pnpm package manager
• MongoDB Atlas account
• Google AI API key
• Auth0 account

1. Clone the repository

git clone https://github.com/yourusername/nexusfolio.git
cd nexusfolio

2. Install dependencies

pnpm install

3. Environment setup

cp .env.example .env.local

4. Configure environment variables

# Database
MONGODB_URI=your_mongodb_connection_string

# Authentication
AUTH0_SECRET=your_auth0_secret
AUTH0_BASE_URL=http://localhost:3000
AUTH0_ISSUER_BASE_URL=your_auth0_domain
AUTH0_CLIENT_ID=your_auth0_client_id
AUTH0_CLIENT_SECRET=your_auth0_client_secret

# AI Services
GEMINI_API_KEY=your_gemini_api_key

# API Configuration
NEXT_PUBLIC_API_URL=http://localhost:3000

5. Run the development server

pnpm dev

6. Open your browser Navigate to http://localhost:3000

nexusfolio/
├── apps/
│   └── web/
│       ├── app/
│       │   ├── api/                 # API routes
│       │   │   ├── chat/            # RAG chat endpoint
│       │   │   ├── portfolio/      # Portfolio data API
│       │   │   └── user-stocks/     # Stock management API
│       │   ├── dashboard/           # Main dashboard
│       │   └── layout.tsx           # Root layout
│       ├── components/
│       │   ├── ai-advisor/         # AI chat components
│       │   ├── stocks-portfolio.tsx # Portfolio display
│       │   └── manual-stock-modal.tsx # Stock addition
│       ├── lib/
│       │   ├── rag-service.ts       # RAG implementation
│       │   ├── portfolio.ts         # Portfolio service
│       │   ├── semantic-search.ts   # Semantic search
│       │   └── vector-store.ts      # Vector database
│       ├── models/
│       │   └── Stock.ts             # MongoDB model
│       └── utils/
│           └── dbConnect.ts          # Database connection

• POST /api/chat - Generate AI responses with portfolio context

• GET /api/portfolio - Fetch user's portfolio data
• POST /api/user-stocks - Add stock to portfolio
• DELETE /api/user-stocks - Remove stock from portfolio

• GET /api/stockQuote - Get real-time stock data
• GET /api/searchStock - Search for stocks

The RAG (Retrieval-Augmented Generation) service combines:

• User Portfolio Data - Actual stock holdings and preferences
• Market Information - Real-time stock data and news
• Semantic Search - Contextual market insights
• AI Responses - Personalized investment advice

• Vector Database for market data retrieval
• Contextual Relevance for better AI responses
• Real-time Updates with live market information

• Auth0 Authentication - Enterprise-grade user management
• Data Encryption - Secure financial data storage
• API Rate Limiting - Prevent abuse and ensure performance
• Input Validation - Sanitize user inputs
• Session Management - Secure user sessions

• Real-time Updates - Live stock data synchronization
• Optimized Queries - Fast database operations
• Caching Strategy - Reduced API calls and improved performance
• Error Handling - Robust error management
• Scalability - Designed for multiple concurrent users

# Run tests
pnpm test

# Run linting
pnpm lint

# Type checking
pnpm type-check

1. Connect your GitHub repository to Vercel
2. Configure environment variables
3. Deploy automatically on push to main branch

# Build the application
pnpm build

# Start production server
pnpm start

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

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

• Google AI for Gemini API
• MongoDB for Atlas database
• Auth0 for authentication
• Next.js team for the amazing framework
• OpenAI for inspiration on RAG architecture

• Documentation: Github Docs
• Issues: GitHub Issues

Built with <3 by the NexusFolio team

Empowering investors with AI-driven insights