How much an AI agent should remember mid-conversation isn't a one-size decision. A dense, multi-part technical question needs the agent to hold a lot of context. A quick factual lookup doesn't, and paying for that extra context is waste. Wonderchat lets you tune the context window instead of deciding for you.
Set a longer context length and the agent carries more of the conversation and the source material as it answers - better for complicated, back-and-forth questions where earlier detail matters. Set it shorter and answers come faster and cost less, which suits high-volume, straightforward queries. You're trading accuracy against speed and cost deliberately, with a dial, rather than accepting whatever default a vendor chose.
Whatever window you set, the agent still answers only from your own content and still cites its source - context length changes how much it holds at once, not where the answers come from. So you get the tuning without giving up the grounding that keeps answers trustworthy.
It's part of a SOC 2 Type II certified, GDPR-compliant platform. For teams running real volume, this is the difference between a bill that scales sensibly and one that doesn't - you decide how much memory each answer is worth.
