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IJONIS
Web & Software

AI Grounding

AI Grounding is the process where AI models base their answers on verifiable, external sources — rather than generating freely. Through grounding, AI search engines reduce hallucinations and deliver fact-based answers with source citations. For businesses, grounding means: those recognized as trustworthy sources get cited.

Why does this matter?

Grounding is the mechanism that determines which sources AI answers cite. AI models with grounding (Google Gemini, Perplexity, ChatGPT with browsing) favor sources with clear facts, structured data, and high authority. Companies that make their content "grounding-friendly" are systematically cited more frequently.

How IJONIS uses this

We optimize your content for grounding: clear factual statements in lead paragraphs, source citations for statistics, structured data as trust signals, and consistent entity information. The goal is for AI models to recognize your website as a trustworthy primary source — not one of many.

Frequently Asked Questions

What makes content "grounding-friendly" for AI?
Grounding-friendly content has: clear, verifiable factual statements (no vague formulations), source citations for numbers and statistics, consistent entity signals (company name, location, expertise), structured data (Schema.org), and a clear content hierarchy that AI models can easily parse.
How are grounding and hallucination related?
Hallucination occurs when AI models invent facts instead of verifying them. Grounding is the antidote: it forces the model to base answers on real sources. AI engines with strong grounding (Perplexity, Google with Gemini) cite your content — and your brand benefits from the trustworthiness.
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