RAG Explorer

An interactive journey through the Retrieval Augmented Generation pipeline — explore each component, understand pitfalls, and master implementation.

Brought to you by RespeakRespeakEnterprise RAG Platform

The RAG Process at a Glance

Phase 1

Data Ingestion

Prepare, clean, and index source data

Steps: 1-6
Phase 2

Retrieval

Find and rank relevant information

Steps: 7-10
Phase 3

Generation

Create and improve responses

Steps: 11-15

Key Benefits of RAG

Reduced Hallucinations

Ground responses in factual data rather than training data memorization

Up-to-date Information

Access fresh data not available during model training

Source Attribution

Provide citations and evidence for generated content

Domain Specialization

Enhance performance on specific topics without fine-tuning

The RAG Pipeline: Step by Step

Phase 3: Generation

Skip the RAG Complexity

Building RAG systems from scratch is challenging. Respeak provides an out-of-the-box RAG platform with cutting-edge information extraction, table parsing, and image understanding.