At its core, Advanced RAG provides developers with a modular architecture to implement RAG workflows. The framework features pluggable components for document ingestion, chunking strategies, embedding generation, vector store persistence, and LLM invocation. This modularity allows users to mix-and-match embedding backends (OpenAI, HuggingFace, etc.) and vector databases (FAISS, Pinecone, Milvus). Advanced RAG also includes batching utilities, caching layers, and evaluation scripts for precision/recall metrics. By abstracting common RAG patterns, it reduces boilerplate code and accelerates experimentation, making it ideal for knowledge-based chatbots, enterprise search, and dynamic content summarization over large document corpora.

SearchUnify offers a comprehensive unified cognitive platform designed to elevate customer support and self-service through AI-powered solutions. It provides enterprise search functionalities, insights engines, and various AI applications to improve information retrieval, issue resolution, and customer engagement. By leveraging multi-platform search, natural language processing, and content gap analysis, SearchUnify facilitates faster, more accurate responses and boosts overall customer satisfaction.