Enhancing Legal Document Analysis with AI Chat Interface

Challenges

• During the parsing of formatted documents, an issue of overfitting to similar structures was identified. To address this, we employed vectorization techniques on repeated sections, enhancing document quality.
• Maintaining robust data security and anonymity was of paramount importance to our clients. To safeguard this, we adapted the vectored documents so that sensitive information, such as names, remains concealed unless authorized by administrators.
• Additionally, we were tasked with developing a restriction for scanned image pages, allowing only English-language images to be processed by the algorithm. This restriction was essential as users could upload various image formats and request algorithmic operations.

• We developed a web application featuring a chat interface that enables users to upload various document types, including Word documents, PDF files, and scanned images. The application provides results tailored to the user's requirements. Pre-defined prompts were allocated for each task, while users also had the option to input their prompts to customize the results.
• For scanned images, our AI engineers applied Optical Character Recognition (OCR) technology to extract text, which was then tokenized and used as input tokens for the Generative AI model. Word documents and PDF files were tokenized directly.
• The system was designed to answer legal document-related queries within a speedy 1-2 second response time. The analysis of the document, regardless of its size, was targeted to be completed within 8-10 seconds.