Every time you open a web chatbot, you are greeted by an empty input field. You are forced to re-introduce yourself, describe your company's product, re-paste design parameters, and explain decisions finalized yesterday.

State-of-the-art models have extraordinary reasoning abilities, but zero memory of your daily reality. That is the fundamental disconnect we are solving.

Frontier models have immense parameter counts, but they lack episodic memory. Each session is an isolated conversation with a stranger.

Engineering Persistent Local Working Memory

In Maple's current development builds, our background daemon continuously creates lightweight semantic vector embeddings of active windows, closed tabs, and meeting transcripts. These embeddings are stored locally in an indexed SQLite database.

Zero Context Tax

When you summon Maple, the active prompt is dynamically injected with the most relevant local context from your past hours and days. You never have to copy-paste background context again.