Loading repository data…
aquacommander / repository
LegalAIProject
⭐The Automated Legal Document Analysis Platform is a powerful web application that automates the laborious process of analyzing legal documents. By leveraging cutting-edge technologies such as Next.js, NLP, and machine learning models, our platform extracts relevant information and identifies potential risks from legal documents⭐
#ai#analysis-platform#docker#flask#legal-ai#machine-learning
Live repository statistics
★ 4Stars
⑂ 0Forks
◯ 0Open issues
◉ 4Watchers
48/100
OPENREPOHUB HEALTH SIGNAL
Mixed signals
A transparent discovery signal based on current public GitHub metadata.
Recent activity35% weight
52
Community adoption25% weight
9
Maintenance state20% weight
100
License clarity10% weight
0
Project information10% weight
75
This score does not audit code, security, maintainers, documentation quality, or suitability. Verify the repository and its current documentation before adoption.
README preview
Legal AI :Automated Legal Document Analysis Platform
Overview
The Automated Legal Document Analysis Platform is a powerful web application that automates the laborious process of analyzing legal documents. By leveraging cutting-edge technologies such as Next.js, NLP, and machine learning models, our platform extracts relevant information and identifies potential risks from legal documents. It empowers users to understand complex contract clauses, avoid potential losses, and make informed decisions when signing contracts.
Key Features
- 📃 Automated Document Analysis: Our platform streamlines the manual process of analyzing legal documents, saving time and effort.
- 📖 Reading Comprehension Model: We have developed and evaluated a reading comprehension model based on the SQuAD dataset, allowing users to extract information directly from the documents.
- 📑 CUAD Dataset: To address critical clauses commonly asked by people and lawyers, we created a CUAD dataset consisting of 500 contracts in the form of question responses.
- ✍️ Paraphrasing Model: We integrate a paraphrasing model based on the T5-base model. This model utilizes datasets from Quora, SQuAD 2.0, and the CNN news dataset, enabling users to better understand contract clauses.
- ⭕ Sentiment Analysis: Our platform includes a sentiment analysis model powered by TextBlob, which provides insights into the impact and implications of contract clauses.
- 💻 User-Friendly Interface: We have developed a user-friendly interface using Next.js, ensuring a seamless and intuitive user experience.
- 🔗 Flask Server Integration: The web interface connects seamlessly to the machine learning side through a Flask server, enabling efficient data processing and analysis.