NextCandle

NextCandle bridges real-world news and stock movements, explaining why markets change and helping users spot patterns, learn trends, and make smarter investing decisions.

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NextCandle

NextCandle is a web-based AI-driven stock analysis platform that helps users predict and visualize market trends.
It integrates real-time stock data with artificial intelligence models to forecast potential movements, summarize market news, and display insights through an interactive and modern interface.

Built with a Next.js frontend and a FastAPI backend powered by Python, NextCandle offers a seamless experience for users seeking fast, data-backed market insights.

Key Features

Stock Analysis & Prediction

  • Users can search for stocks and receive AI-generated predictions about price movements, sentiment, and trends.
  • Historical data and analysis history are stored in MongoDB for quick retrieval and visualization.

AI-Powered Insights

  • Analytical models in analyzer.py process financial data to generate intelligent summaries.
  • Sentiment analysis and keyword extraction help identify market tone and emerging topics.

News Integration

  • Pulls the latest market news for each company or stock symbol.
  • Produces concise AI-driven summaries and sentiment polarity scores.

User-Friendly Dashboard

  • Clean and responsive design built with Next.js and Tailwind CSS.
  • Displays interactive charts, performance summaries, and data visualizations.
  • Enables intuitive navigation between stock analysis, market news, and saved user data.

How It Works

  1. Data Retrieval
    The user inputs a stock symbol (e.g., AAPL). The frontend sends this query to the backend API.

  2. AI Analysis
    The FastAPI backend (in main.py and analyzer.py) processes data and executes AI models to generate predictions and summaries.

  3. Data Storage
    MongoDB stores user analyses, summaries, and insights for future visualization.

  4. Display
    The Next.js frontend (in src/app/analysis/page.tsx) retrieves and renders AI-generated insights, charts, sentiment data, and summaries.

Technologies Used

Frontend

  • Next.js 14 — Modular app router architecture
  • React 18 — Component-based UI framework
  • TypeScript — Type safety and scalability
  • Tailwind CSS — Utility-first responsive styling
  • shadcn/ui — Prebuilt UI components for design consistency
  • Recharts — Visualization for financial data

Backend

  • FastAPI — High-performance Python API framework
  • Supabase — Optional authentication and database integration
  • MongoDB (motor) — Asynchronous NoSQL storage
  • dotenv — Environment variable management
  • Uvicorn — ASGI server for production or local use

Challenges Faced and How They Were Overcome

Synchronizing Backend and Frontend Data

🔗 Synchronizing Backend and Frontend Data

Challenge:
Ensuring smooth communication between the FastAPI backend and the Next.js frontend without latency or data mismatches.

Solution:
Used Supabase for real-time user authentication and session management, and MongoDB for persistent data storage and synchronization across user sessions.
This combination allowed reliable communication between the backend API and the frontend, ensuring that data, analytics results, and user history remained consistent and up-to-date.

Managing Authentication

Challenge:
Integrating Supabase-based authentication while maintaining persistent user sessions.
Solution:
Developed a modular useAuth.ts hook to handle login, registration, and session validation efficiently.

⚡ Handling Real-Time Updates

Challenge:
Ensuring analysis results stay current with new market data.
Solution:
Implemented client-side polling and React state updates, allowing data to refresh seamlessly without reloading the page.

Frontend Consistency

Challenge:
Designing a visually cohesive interface across multiple modules (stocks, news, insights).
Solution:
Used Tailwind CSS and shadcn/ui to maintain a clean, consistent, and responsive UI with minimal custom CSS.

Future Improvements

  • 🧠 Google Gemini ADK Integration:
    Add support for the Google Gemini ADK to enhance natural language reasoning, predictive analytics, and market forecasting.

  • 📲 Push Notifications:
    Integrate Firebase Cloud Messaging (FCM) to send alerts for stock movements, AI predictions, and breaking financial news.

👥 Team

Name Role
Dylan AI / Backend
Sami Data Scraping / Backend
Manny Database / Backend
Andres UI & UX /Frontend

🌍 Acknowledgements

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