The course provides a comprehensive guide to optimizing retrieval systems in large-scale RAG applications. It covers tokenization, vector quantization, and search optimization techniques to enhance search quality, reduce memory usage, and balance performance in vector search systems.

Geometric methods for hallucination detection in RAG systems, based on angular relationships in embedding space.

Official implementation of "Anti-Rumor Context Integration: A Novel RAG System for Automated Factual Correction". Features multi-tier retrieval (Internal KB → Google Fact Check API → Live Web Search), hybrid semantic-keyword scoring, constrained T5 counter-narrative generation, and an XAI explainability module.

A comprehensive RAG (Retrieval-Augmented Generation) system for employee onboarding at ChemCorp Industries, a chemical manufacturing company. This system provides instant answers to employee questions by leveraging vector databases and large language models.

Secure HyDe RAG is an in-house RAG application designed for querying complex technical documentation (SOPs, RCA-CAPA, Engineering Manuals) with high precision.