Gurgaon, Haryana, India
Summary
Developed and optimized AI-powered Retrieval-Augmented Generation (RAG) applications, enhancing information retrieval and user experience for large-scale document processing.
Highlights
Architected and developed a robust RAG application, efficiently processing and retrieving information from large PDF document volumes using vector-based search and LLM-driven responses.
Implemented end-to-end data processing pipelines to extract text, generate embeddings with state-of-the-art models, and store vectors in a scalable vector database for efficient similarity search.
Engineered a customized knowledge base, enhancing contextual understanding and improving response accuracy by providing domain-specific insights.
Optimized query response time by 30-40% through advanced similarity search algorithms, significantly accelerating information retrieval compared to traditional methods.
Ensured seamless user experience by developing a scalable solution capable of handling thousands of PDFs and concurrent user queries with minimal latency.