Overview
A hallucination occurs in an AI model when the system generates an answer that is confident but incorrect, partially fabricated, or not supported by any real source of information. In other words, the model produces output that sounds plausible but isn’t true, even though it presents the answer as fact.
This happens because Large Language Models (LLMs), like those that drive general use chatbots like ChatGPT and Gemini, don’t inherently “know” facts—they generate responses by predicting the most likely sequence of words based on patterns learned during training. When the model:
Lacks the specific information needed
Is given a vague or incomplete prompt
Encounters a question outside its training data
Tries to fill in gaps to be helpful
It may produce an answer that looks right but has no grounding in actual data. This is a hallucination. Public LLMs are especially prone to this because they are not connected to your institution’s verified information and cannot check whether their answers are correct.
How is Element451’s Bolt AI different from ChatGPT or Gemini?
General-purpose LLMs do not know your institution, data, or policies unless that context is provided. Bolt AI grounds factual responses in the sources available to the feature: your Knowledge Hub, permitted Element451 or CRM context, and Element-provided context. Agent and Custom Skill instructions guide behavior and actions; they are not factual sources. When reliable information is unavailable, Bolt Agents are instructed to say they do not know rather than guess.
What does Element451 do to prevent hallucinations?
We use several layers of accuracy controls:
Grounding: Factual answers are grounded in the Knowledge Hub and permitted CRM or Element451 context available to the feature. Element-provided prompts and configured Agent or Custom Skill instructions guide behavior and actions; they are not themselves verified factual sources.
RAG (Retrieval-Augmented Generation): We retrieve and rank the most relevant content before generating a response.
Guardrails: Internal prompts instruct the AI to say “I don’t know” if the information can’t be confirmed.
Citations: In Bolt Discovery and Bolt AI agent chats, we cite the public knowledge source when available to provide additional information discoverability and confidence in the answers provided.
Can hallucinations still happen?
Yes—no LLM can reach 100% but Element451 consistently achieves a high level of accuracy. Most issues occur when:
Knowledge Hub content is outdated, incorrect, or lacks sufficient context.
Underlying data is incomplete
A temporary bug affects retrieval
Keeping your Knowledge Hub up to date supports the best results. AI accuracy is only as strong as the information it uses. If the information in the Knowledge Hub is wrong or incomplete, the answer may be wrong; if it is complete and current, Bolt AI can respond more reliably.
If you see problematic answers or responses, reviewing your Knowledge Hub content is a good place to begin.