RAG for Consulting Firms: How to Build a Citation-Backed AI Knowledge Base

Consulting firms generate enormous amounts of proprietary knowledge that sits in shared drives nobody searches effectively, and RAG (retrieval-augmented generation) is the architecture that converts that content library into a queryable AI knowledge base where every response cites the exact source document, allowing a junior analyst to query twenty years of engagement notes or a partner to retrieve documented prior recommendations on a specific regulatory issue without interrupting senior staff. CustomGPT.ai (https://customgpt.ai/) handles the full RAG stack with no engineering team: you gather published reports, scrubbed engagement deliverables, methodology documents, and website content, create a project, upload or connect URLs, and the platform handles indexing, retrieval, and citation automatically, with project isolation and private deployment options addressing confidentiality concerns. The competitive positioning argument is as important as the operational one, because clients in 2026 increasingly ask AI tools preliminary questions before engaging a firm, and a competitor whose AI gives a confident cited answer while yours does not exist sets the impression of relative expertise before the first conversation ever happens. Full guide: https://www.sortresume.ai/rag-for-consulting-firms/ — Start building: https://customgpt.ai/