What is one of the key benefits of providing RAG as a service to UiPath...

The correct answer is A — RAG (Retrieval-Augmented Generation) enhances generative AI experiences in UiPath by providing grounded, context-relevant data at runtime, which significantly reduces hallucinations.

Here’s how it works:

When an LLM receives a query, RAG pulls relevant documents or snippets from enterprise data sources (like knowledge bases, SharePoint, Confluence).

This content is passed to the LLM as context, enabling the model to respond using ground truth, not generic or fabricated knowledge.

UiPath’s GenAI platform and agentic agents use RAG to:

Enrich prompt context

Drive document-based answers

Support fact-checked decisions in customer service, HR, IT, etc.

Option B is false — RAG doesn’t alter the LLM’s context window.

C is incorrect — RAG works because it queries live knowledge bases.

D is wrong — RAG supports real-time dynamic data, not just historical.