Enhancing Legal Document Processing with Retrieval-Augmented Generation (RAG) In the legal industry, the ability to efficiently retrieve and analyze relevant information from extensive document collections is critical. Traditional methods of processing and searching through legal documents are often time-consuming, labor-intensive, and prone to errors. This case study highlights the implementation of a Retrieval-Augmented Generation (RAG) application, designed to enhance the accuracy and speed of legal document retrieval, ultimately improving workflow efficiency. GenAI and Machine Learning View Project View All Projects
An OCR-Driven Pipeline for SQL Based RAG Applications Organizations often face significant challenges when extracting and analyzing large amounts of tabular data embedded in PDFs, a common format for business documents. This case study presents a technology solution that leverages Optical Character Recognition (OCR) to extract tabular information from PDFs, normalizes it, and loads it into a SQL database. GenAI and Machine Learning View Project View All Projects
VividCloud Extends Rockstep's Backend Architecture & Develops an Application Interface to Meet the Complex Needs of Research Scientists Rockstep Solutions is an early-stage company in the healthcare technology market. Healthcare View Project View All Projects