Auto‑RAG
Automates the retrieval and prompt assembly steps so your app consistently selects the best context with minimal manual tuning.
What Auto-RAG Means for Your Business
Auto-RAG saves money by only searching your knowledge base when needed, making responses faster and cheaper for high-volume interactions.
The Cost-Saving Power of Smart Retrieval
How It Works
Instead of searching your entire knowledge base for every question, Auto-RAG learns which information to keep "in memory" and which requires a database lookup.
- • Stores common questions and answers locally
- • Only searches when specific details are needed
- • Reduces API calls and response times
- • Maintains accuracy while cutting costs
Real Business Example
E-commerce Customer Service:
An e-commerce site's AI knows basic shipping info by heart but only searches the inventory database when asked "Do you have size 10 Nike Air Max in red?"
Result: Saves API costs on simple questions while providing instant answers for complex inventory queries.
Bottom Line: Auto-RAG is perfect for businesses with high customer interaction volumes where you want to maintain quality while reducing operational costs.
Overview
Auto‑RAG aims to automatically choose chunk sizes, retrieval depth, filters, and prompt templates based on the user query and past evaluation results. It reduces manual engineering effort and keeps quality steady as your corpus grows.