Legal Hearing Summarizer

Leverage AI to streamline document review. Upload legal documents and get concise summaries. Built with Flask, Azure Document Intelligence, and Next.js for a seamless experience.

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Legal Hearing Summarizer

Inspiration

Legal hearings often involve lengthy transcripts, making it time-consuming for lawyers, judges, and legal professionals to extract key information. We wanted to streamline this process by leveraging AI-powered summarization, reducing hours of manual work to just seconds.

What it does

Legal Hearing Summarizer is a web-based application that processes legal hearing PDFs and generates concise summaries. Users upload a legal document, and our system extracts key details, such as case arguments, judgments, and important points, using AI.

How we built it

  • Backend: Flask (handles file processing, AI model interaction)
  • Frontend: Next.js (provides a seamless user experience)
  • Azure Document Intelligence for OCR and document parsing
  • GPT-3.5-Turbo via OpenAI API for generating structured summaries ### GitHub Copilot in Our Development Process

We leveraged GitHub Copilot throughout the development of our Legal Hearing Summarizer, significantly accelerating our coding process and improving efficiency.

How GitHub Copilot Assisted Us

  • Code Autocompletion – Helped us write Flask and Next.js functions faster by predicting and suggesting entire code blocks.
  • API Integration – Provided intelligent suggestions when integrating Azure Document Intelligence and GPT-3.5-Turbo, reducing syntax errors and improving efficiency.
  • Flask Backend Development – Assisted in structuring API endpoints, handling file uploads, and processing PDF data seamlessly.
  • Next.js Frontend Components – Helped generate reusable UI components and optimized state management for a smooth user experience.
  • Debugging & Refactoring – Suggested improvements for cleaner, more efficient, and maintainable code, reducing technical debt.

By using GitHub Copilot, we streamlined our development workflow, allowing us to focus more on problem-solving and innovation rather than spending excessive time on boilerplate code.

Challenges we ran into

  • Processing complex legal jargon while maintaining accuracy.
  • Optimizing Azure Document Intelligence for different PDF formats
  • Ensuring the AI-generated summaries were both concise and legally coherent

Accomplishments that we're proud of

  • Successfully integrating AI to automate legal document summarization
  • Building an intuitive and efficient web app with a smooth user experience
  • Processing and summarizing legal hearings within seconds

What we learned

  • Leveraging Azure AI services for document processing
  • Fine-tuning AI prompts to extract structured legal information
  • Optimizing a full-stack web application using Flask and Next.js

What's next for Legal Hearing Summarizer

  • Enhancing AI models for better context understanding
  • Adding support for multiple legal document formats
  • Implementing multi-user collaboration and case tracking

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