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Concepts

Grounding

The process of connecting AI model outputs to verified, real-world information sources. Grounded AI responses cite specific documents, databases, or web sources — reducing hallucinations and increasing factual reliability.

Why it matters

Grounding is one of the most effective ways to make AI trustworthy, because it ties answers to real, checkable sources instead of the model's memory alone. This sharply reduces confident-sounding mistakes, which matters enormously in fields like law, medicine, and research where a wrong fact has real consequences. When an assistant shows you where its answer came from, you can verify it rather than simply hoping it's right.

In practice

You ask an AI tool about your company's refund policy. A grounded system searches your actual policy document, quotes the relevant clause, and links to it, rather than guessing from general training. A useful habit: prefer tools that cite their sources and then click through to confirm, especially for anything factual, financial, or medical where being confidently wrong could cost you.

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Put Grounding into practice

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