AI Contract Summarizer
Project Overview
This project focuses on simplifying the way people read and understand long legal contracts.
Using AI, it converts complex documents into short, clear summaries so users can quickly grasp the important points.
Project Vision
Reading contracts manually takes a lot of time and requires attention to detail. Missing even a small clause can lead to serious consequences.
This project aims to solve that by using AI to automatically highlight key information, making contract analysis faster, easier, and more reliable.
Implementation Details
- Created a structured backend using object-oriented programming
- Built a system to read and extract text from PDF files
- Processed the text by cleaning and dividing it into manageable chunks
- Used an AI model to generate summaries from the extracted content
- Formatted the output for better readability
- Tested the system using a simple input-based interface
Learnings
- Gained practical understanding of how AI models summarize text
- Learned how to handle real-world unstructured data like PDFs
- Improved skills in designing clean and modular code
- Understood the importance of prompt design for better AI outputs
- Built confidence in developing end-to-end AI projects
Result
The final system can successfully reduce large contracts into short summaries, helping users save time and make faster decisions.
Tools & Technologies
- Python – Used to build the core logic and AI pipeline
- PyPDF – Helps in extracting text from contract PDFs
- LLM APIs – Generates accurate summaries using AI
- NLTK / SpaCy – Used for text cleaning and preprocessing
- OOP Design – Keeps the code modular and maintainable
- HTML & CSS – Builds a responsive and clean user interface