RAG Analytics Services
Packages & Pricing.

RAG analytics services to measure retrieval quality

RAG analytics services show whether your retrieval-augmented chatbot finds the right passages and whether its answers stay grounded. Omeiro tests with question sets, scores retrieval and hallucination rates, and tunes similarity thresholds so answers improve in measurable steps.

Without measurement, every prompt tweak is a guess. With it, you see what each change did.

RAG analytics: testing retrieval before users do

RAG analytics begins with a test set. Collect real questions users ask, along with the documents that should answer them, so retrieval quality can be scored against a known right answer. Share how documents are chunked, which embedding model and vector store you use, and your prompt. Questions with no answer in your content are valuable too, since they show whether the system admits a gap or invents one.

A common mistake is judging a RAG system by a few demo questions. RAG analytics here measures whether the right passages are retrieved, whether the answer stays faithful to them and where thresholds let in irrelevant text. Findings are specific, such as chunks that are too long or a similarity cutoff set too low. Automated checks on the top tier rerun after each change, so a regression is caught early.