core service
rag development
retrieval-augmented generation (rag) allows large language models to securely read your private documents, databases, and wikis before answering a question—drastically reducing hallucinations.
build your rag pipelinewhy use rag instead of fine-tuning?
real-time updates
unlike fine-tuning which requires expensive retraining every time data changes, a rag system instantly uses updated documents as soon as they are added to the vector database.
source attribution
rag models can cite the exact document and paragraph they used to generate an answer, providing auditability and trust that fine-tuning cannot offer.