End RAG Sprawl: The case for platform standardization

Retrieval Augmented Generation (RAG) has become a standard practice within enterprises to enhance AI generation by retrieving relevant, trusted information, but its widespread adoption has led to challenges such as RAG sprawl. This sprawl results from each enterprise function implementing its own RAG system, causing inefficiencies, disconnected data management, and security concerns. To address this, a trend is emerging toward standardizing on a few selected platforms, with many enterprises evaluating options provided by their current cloud providers and choosing partners for their RAG strategy. Key factors in selecting these platforms include flexibility, scalability, security, future-proofing, and vendor viability. Vectara has emerged as a notable partner for its focus on providing an end-to-end AI platform that emphasizes accuracy, hallucination prevention, and scalability, helping enterprises address RAG sprawl and achieve their AI transformation goals.