Tokens
Tokens are the small chunks of text, often words or parts of words, that an AI model reads and generates when processing language.
Tokens are the basic units of text an AI model works with. A token can be a whole word, a part of a word, a punctuation mark, or a space. Models do not read characters or sentences directly; they break text into tokens first, then process those.
Tokens matter because they are how model limits and costs are measured. The size of a context window is counted in tokens, and the length of both the input and the generated reply is also counted this way. As a rough guide, a token tends to be shorter than a full word.
In context
In customer support, token counts shape how much of a conversation and how many help articles an AI assistant can take in before answering. A long chat thread, several reference documents, and the customer's question all consume tokens, and together they must stay within the model's limit.
Token usage also affects response speed and operating cost. Trimming irrelevant text, summarizing long histories, and retrieving only the passages that matter keep token counts manageable, which keeps replies fast and grounded in the right information.
How Auralis uses Tokens
Auralis manages token usage by retrieving only the most relevant Knowledge Center passages for each question, so Answer and Assist respond quickly while staying grounded in your approved content.