Retrieval-Augmented Generation (RAG) is the fastest way to give AI models your company's private knowledge without retraining from scratch.
When RAG Wins
RAG outperforms fine-tuning when the knowledge base changes frequently or is too large to embed directly.
Case Study
We built a legal-document AI assistant with 97% accuracy, powered by a vector database and custom retrieval logic.
Done right, RAG turns AI from "generic" to "specialist."
