Demo - Progress Agentic RAG - Product Builders Guide

Building a production-ready Retrieval-Augmented Generation (RAG) system requires far more than connecting a large language model to your content. This video breaks down every major component involved in delivering trustworthy AI answers: • File ingestion • OCR for scanned content • Audio and video transcription • Chunking and embeddings • Vector indexing • Hybrid search • Prompt orchestration • Citation-based retrieval • Evaluation and groundedness scoring • Deployment and embedding See how Progress Agentic RAG manages the entire pipeline while providing visibility into answer quality, retrieval performance, and AI costs. Whether you're building an AI-powered help center, support experience, knowledge portal, or customer application, this demonstration shows how to move from content to answers without managing a complex AI stack. #RAGArchitecture #AgenticRAG #EnterpriseSearch #VectorDatabase #LLMOps #AIEvaluation #SemanticSearch #KnowledgeBox #AIEngineering #GenerativeAI #MachineLearning #EnterpriseTech