IntelliQuery is an AI-powered content aggregation platform that retrieves relevant images, videos, and generates high-quality articles based on user queries. It seamlessly integrates multiple data sources to provide an enriched multimedia search experience. Additionally, it features intelligent document processing and conversational AI, allowing users to upload text or PDF files for automatic summarization and interact with a chatbot for real-time insights.
- AI-Powered Content Generation 📝: Generates high-quality articles based on user queries.
- Multimedia Integration 🎥🖼️: Fetches relevant images and videos from multiple data sources.
- Conversational AI 🤖: Chatbot for real-time insights and contextual information retrieval.
- Intelligent Document Processing 📄: Supports text and PDF uploads for automatic summarization.
- Cloud Storage ☁️: Utilizes Amazon S3 for secure file management.
- Scalable Architecture ⚙️: Built with AWS Lambda for efficient serverless computing.
- Flutter 📱: Cross-platform UI development for seamless user experience.
- Node.js ⚡: Backend services ensuring robust API interactions.
- PostgreSQL 🗄️: Efficient database management for storing content and user data.
- Generative AI 🧠: AI-driven content and insight generation.
- AWS Lambda ☁️: Serverless architecture for scalable backend processing.
- Amazon S3 📂: Secure cloud storage for document management.
- REST API 🔗: Facilitates communication between the frontend and backend.
- Clone the repository:
git clone https://github.com/TanishaMehta17/IntelliQuery
- Get the dependecy:
flutter pub get
- Run the project:
flutter run
We welcome contributions to GitGenie! To contribute:
- Fork the repository.
- Create a new branch for your feature or fix.
- Make your changes and ensure they follow project guidelines.
- Commit your changes with clear messages.
- Push to the branch on your fork.
- Open a pull request for review.
For questions or support, please contact tanishamehta1709@gmail.com.
Give a ⭐ if you like this project!