Context window
The maximum amount of text, measured in tokens, that an AI model can read and consider at one time when generating a response.
Context window is the span of text an AI model can hold in working memory during a single request. It is measured in tokens, which are the small chunks of text a model reads. Everything the model needs to consider, including the user question, prior conversation, and any supporting documents, has to fit inside this limit.
When the combined input exceeds the window, older or less relevant material gets dropped or summarized. A larger context window lets a model reason over longer conversations and more reference material at once, while a smaller one forces tighter selection of what to include.
In context
In customer support, the context window decides how much of a conversation and how many knowledge articles an AI assistant can use to answer a question. A wider window means the model can read a full back and forth thread, the customer's account details, and the relevant help documents together, which produces more accurate and consistent replies.
When a window is too small, the assistant can lose track of what a customer said earlier in a long chat, ask for information already provided, or miss a policy detail buried in a long document. Support teams manage this by retrieving only the most relevant passages rather than feeding in entire knowledge bases.
How Auralis uses Context window
Auralis keeps each customer reply grounded by retrieving only the most relevant passages from your Knowledge Center into the model's context window, so Answer and Assist stay accurate without filling the window with unrelated content.