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Glossary

What is Grounding?

Updated September 2026TechnicalIntermediate

Definition

Grounding is the practice of tying a model’s answer to specific source documents so each claim traces back to something actually retrieved. Unlike retrieval-augmented generation, which describes the architecture that fetches those documents, grounding describes the standard the answer is held to. A grounded answer is checkable, an ungrounded one is a guess.

At a glance

  • CategoriesTechnical
  • Related fieldsAI Search
  • DifficultyIntermediate

At a glance

  • Grounding constrains a model to what the retrieved documents say, not what it remembers.
  • A citation is evidence of grounding only if the cited page supports the sentence beside it.
  • Grounding is a matter of degree: parts of one answer can be grounded while others are not.
  • Pages stating facts plainly, with dates and sources, are easier to ground against and get used more.

Tying a claim to a document

The system retrieves passages, puts them in front of the model, and instructs it to answer from those passages rather than from memory. Google Cloud’s grounding overview describes this as connecting the model to a verifiable source of information, and the original RAG paper set out the architecture that made it practical.

Then it checks, or tries to. Some systems run a verification pass mapping each sentence back to a supporting passage and flagging anything unsupported. Others rely on the instruction alone.

Gaps are where it breaks. If the retrieved passages cover most of what a question needs, the model still writes a complete answer. The missing part comes from training data, arrives in the same confident tone, and often sits beside a citation belonging to the sentence next to it.

Groundedness decides who gets named

Every brand asks how to get cited. The more useful question is which of your claims a machine could defend if challenged.

A generative system prefers passages it can point at without risk. “Our jackets are highly breathable” grounds nothing, because it supports no specific claim. A sentence giving the membrane rating, the test standard and the date grounds cleanly, and the system reaches for it.

That is why thin, confident marketing copy underperforms in retrieval-augmented generation even when it ranks well. The page is retrievable but not usable, while a plain spec table nobody visits gets quoted week after week.

The logic runs in reverse too. When nothing groundable exists about your brand, the model fills the gap from memory, which is where a hallucination about your products comes from.

Make your pages easy to ground against

Groundability is a property of sentences. You can improve it this week.

  1. Turn adjectives into measurements. “Long battery life” grounds nothing. “Rated for a full working day of continuous use, with the test date printed beside it” grounds a claim.
  2. Attach a source to every figure you publish, including your own. Say who counted, when, and over what sample. Unattributed numbers get skipped.
  3. Give every product a facts block in plain HTML: materials, dimensions, compatibility, warranty. Boring, structured and quotable beats persuasive prose.
  4. Fix contradictions between your own pages. When two of your pages disagree, a careful system uses neither and a careless one picks at random.
  5. Date your claims visibly. A groundable fact with no date decays into an ungroundable one.

Frequently asked questions

  • Is grounding the same as retrieval-augmented generation?

    They are related but not the same. Retrieval-augmented generation is the mechanism: fetch documents, pass them to the model, generate from them. Grounding is the goal that mechanism serves, namely that the output stays faithful to those documents. You can build a RAG system whose answers are poorly grounded, and people frequently do.

  • Does a citation prove an answer is grounded?

    No, and this catches people out. A citation shows the system associated a source with a passage. It does not confirm the source supports the claim. Assistants attach plausible links to sentences they partly invented. If the claim matters, open the link and read it.

  • Can I make my brand easier to ground?

    Yes, and it is one of the few things here you fully control. Publish specific, dated, attributed facts in plain text, and keep them consistent across your site, your profiles and third-party listings. Consistency across sources is what lets a system state something about you without hedging.

  • Does better grounding mean AI search is now reliable?

    Not yet, and it is worth saying plainly. Grounding cuts the error rate without removing it, and a grounded-looking answer can still misread the source it cites. Where being wrong is expensive, treat an AI answer as a lead to check. Deep research modes help because they read more widely, not because they are certain.