Definition
Grounding is the practice of anchoring an AI model's answer in real, retrieved sources rather than letting it rely only on memory. It is what lets an engine cite where its information came from.
On this page
At a glance
- Categories Technical
- Related fields AI Search
- Difficulty Intermediate
How Grounding Works
A model left to its own devices answers from training, which can be stale or wrong. Grounding feeds it fresh, relevant documents at answer time and tells it to base the response on those. That is why retrieval-based engines can handle recent events and show their sources. It is also the main defense against confidently wrong answers.
Why Grounding Matters
Grounding is the moment your content can enter an answer. If the engine retrieves and trusts your page as a grounding source, your information shapes what it tells the user.
Frequently Asked Questions
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Is grounding the same as RAG?
Closely related. Retrieval-augmented generation is the common method used to ground a model in retrieved sources.
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Does grounding remove errors?
It reduces them by tying answers to real sources, but it does not eliminate them entirely.