AI hallucination
An AI hallucination is a confident but false statement produced by a language model — an answer that sounds plausible but isn’t grounded in any real source, such as an invented price, policy, or fact.
How it works
Language models generate text by predicting what’s likely to come next, not by looking anything up. Left to answer from memory alone, they can fill gaps with fabrications that read as fluent and certain.
The most reliable defense is grounding: force the model to answer only from retrieved, trusted content, and have it decline when the answer isn’t there — rather than letting it improvise.
How SiteMind uses it
SiteMind is designed to avoid hallucination by construction. It answers only from your content, and when a relevant passage isn’t found it returns a fixed “I couldn’t find that information on the website” reply — with no model call at all, so there’s nothing to invent.
Related terms
Retrieval-Augmented Generation (RAG)
Retrieval-Augmented Generation (RAG) is a method where an AI looks up relevant information from a trusted source before answering, so its replies are grounded in facts instead of guesses.
Source grounding
Source grounding means every answer an AI gives is tied to and backed by specific retrieved content, and can be traced back to it.
Prompt injection
Prompt injection is an attempt to trick an AI into ignoring its instructions by hiding malicious commands in the text it reads.
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