Your documents already know the answers.

This is RAG — retrieval-augmented generation: the technique behind AI assistants that answer from your business documents instead of guessing. Watch how it works, step by step.

We run this stack ourselves — the assistant on our Ozvyo Agent page answers from a knowledge base built exactly like this.

Watch the pipeline ↓Try our live agent

The pipeline, step by step

START

Step

collect your documentsPrice lists, SOPs, quotes, policies — as they are

Step

split into chunksSmall passages an AI can search precisely

Step

index by meaningSo questions match meaning, not just keywords

Step

retrieve what is relevantA question pulls only the passages that matter

Step

answer with citationsThe AI writes from those passages — and shows its sources

END

The question

What does the Local Visibility System cost?

What RAG retrievespricing.md

Local Visibility System — RM 2,000 setup + RM 599/mo (SGD 990 setup + SGD 199/mo). Up to 10 pages, managed monthly.

The answer, grounded

RM 2,000 setup + RM 599/mo (SGD 990 setup + SGD 199/mo), up to 10 pages, managed monthly. (Source: pricing)

Why this beats a plain chatbot

Answers stay yours

Grounded in your documents, not internet guesses. Your prices, your policies, your wording.

Wrong answers get rarer

Every answer points back to the passage it came from — so you can check it.

Works where your team works

Behind a website chat widget, an internal tool, or the systems we build for you.

RAG doesn't make AI perfect — it makes it checkable. Sensitive answers still get human review, and we say so before we build anything.

SEE IT LIVE

Ask our agent — it runs on this exact pipeline.

Try the Ozvyo Agent Or talk to a human