How a graph-memory proxy sits between your app and the OpenAI API, quietly remembering everything your LLM would otherwise lose.
Every conversation with a large language model starts from zero. Close the tab, start a new session, and the model has no idea who you are, what you discussed yesterday, or what you decided last week. Most tools work around this by stuffing more and more chat history into the context window — which is expensive, slow, and eventually hits a hard limit.
I built TokenMizer to solve this differently: instead of remembering by re-reading everything, it remembers by building a graph.
The Core Idea: A Proxy, Not a Plugin
TokenMizer sits as a proxy in front of any OpenAI-compatible API. Your application doesn't change how it calls the model — it just points its API base URL at TokenMizer instead of directly at OpenAI. Every request and response passes through, gets analyzed, and gets stored before continuing on to the real model.
