Retrieval and search
What is RAG
RAG stands for Retrieval-Augmented Generation: generating answers with information retrieved at runtime.
Short definition
RAG is a way of making a model answer with support from relevant external content instead of relying only on what it learned during training.
What it means
Instead of responding only from model memory, RAG first retrieves useful information and then uses it as context to answer better.
How to understand it better
It is helpful when knowledge changes often or when the response must reflect business data such as catalog content, schedules, rules, or operational state.
How Dialo.ar uses it
In Dialo.ar it matters when the agent needs to ground its answer in business context or relevant signals before building a reply for sales or support.
Frequently asked questions
No. It complements the model with information retrieved at query time.
Because it helps answer with business-specific data instead of only generic knowledge.
Want to see these concepts applied to a real operation?
Dialo.ar combines search, context, and concrete actions to resolve sales and support flows with AI.