Glossary
No jargon for its own sake. Clear definitions of the concepts that make an AI assistant accurate and trustworthy — and how SiteMind uses each one.
Terms
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.
Read definitionEmbeddings turn text into lists of numbers that capture its meaning, so a computer can tell which pieces of content are about the same thing.
Read definitionChunking is the process of splitting long content into smaller, self-contained pieces so an AI can retrieve exactly the relevant part instead of a whole page.
Read definitionA vector database stores content as embeddings and can instantly find the pieces whose meaning is closest to a query.
Read definitionSemantic search finds content by meaning rather than exact keywords, so it can match a question to the right answer even when the words differ.
Read definitionAn AI hallucination is when a model states something false or made-up as if it were true — a serious risk for any customer-facing chatbot.
Read definitionSource grounding means every answer an AI gives is tied to and backed by specific retrieved content, and can be traced back to it.
Read definitionPrompt injection is an attempt to trick an AI into ignoring its instructions by hiding malicious commands in the text it reads.
Read definitionGenerative Engine Optimization (GEO) is the practice of making your content easy for AI systems to find, understand, trust, and cite when they answer questions.
Read definitionSiteMind puts every one of these concepts to work answering your customers. Try it free for 3 days, no card required.