Source Grounding & Citations
Source grounding ensures every AI claim is directly supported by retrieved website text and includes clickable citations for instant human verification.
Source grounding is the enforcement mechanism ensuring an AI model generates responses derived strictly from retrieved reference documents, accompanied by deep-link citations back to the source material.
How Grounding works in practice
Unconstrained AI models generate plausible-sounding text from memory. Grounding constrains the generation phase by instructing the model to synthesize answers exclusively from provided context snippets.
When an answer is synthesized, the system matches generated assertions back to the original source URL and paragraph, providing transparent citation badges in the chat interface.
How SiteMind implements Grounding
Every answer delivered by SiteMind includes clickable source citations linking directly to the exact page where the information was crawled, eliminating user skepticism.
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Related Technical Concepts
AI Hallucination
An AI hallucination occurs when an LLM confidently generates incorrect, fabricated, or non-existent facts not grounded in real source data.
Retrieval-Augmented Generation (RAG)
Retrieval-Augmented Generation (RAG) is a technique where an AI fetches verified passages from a knowledge base before answering, ensuring grounded, factual replies.
Cosine Similarity Thresholds
Cosine similarity measures the angle between two embedding vectors in multidimensional space to determine how closely their meanings match.
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