The Memory Protocol

The Memory Protocol is our proprietary data pipeline that extracts, structures, and prunes long-term context from your logs to feed our relational AI companion, ARIA.

Why a Memory Protocol?

Large Language Models (LLMs) are stateless. To simulate memory, standard applications typically send your entire chat history with every prompt. However, this is token-heavy, costly, and lacks cognitive structure.

The Memory Protocol solves this by parsing your daily reflections into a Personal Knowledge Graph (PKG).

How it works

The pipeline runs in four stages:

1. Entity Extraction: When you save a journal entry or mood check-in, the system parses the text for entities (e.g. `Work`, `Sleep`, `Yoga`) and emotional states.
2. Relationship Mapping: The system draws links (edges) between these entities (e.g., `Yoga` -> `improves` -> `Sleep Quality`).
3. Graph De-duplication: The new nodes are merged with your existing graph to avoid duplicates, updating the weight of active nodes.
4. Context Synthesis: When you chat with ARIA, the system fetches your active graph nodes and summarizes your current "life chapter" in the prompt, allowing ARIA to reference your habits naturally.

For more details on how these services are hosted, see [System Architecture](/docs/architecture).