RAG Application Development

RAG Application Development overview

This service builds a retrieval pipeline around approved sources, structured chunks, metadata, ranking, citations, fallback behavior, and evaluation rather than relying on model memory alone.

Practical scope

• Document chunking and indexing
• Knowledge retrieval before answer generation
• Source-aware answers
• Access and review controls

Implementation approach

RAG application planning defines approved sources, ingestion, hierarchical and semantic chunking, metadata, embeddings, retrieval order, parent resolution, answer composition, citations, and fallback behavior.

Safeguards

RAG safeguards should enforce source and user permissions, reject weak retrieval, preserve citations, resist prompt injection, bound conversation memory, and evaluate answers against approved test questions.