The Adam framework introduces a 5-layer architecture for persistent memory and identity in AI agents. This system is designed to ensure that an AI's identity and accumulated knowledge remain intact, even if the underlying AI model, vendor service, or hardware environment changes. The core principle is 'identity sovereignty,' where an AI's memory is stored in user-owned, human-readable files (e.g., Markdown) on local hardware, rather than being tied to cloud-based services.
The five layers of the Adam framework include: 1. **Vault injection:** Manages the input of information into the memory system. 2. **Memory-core plugin:** Handles memory search and retrieval functions. 3. **Neural graph:** A network of over 7,219 neurons and 29,291 synapses for contextual memory. 4. **Nightly reconciliation:** A process, utilizing Gemini, to reconcile and update memory. 5. **Coherence monitor:** Actively monitors the coherence of the AI's memory during sessions.
The framework has undergone production validation across more than 353 sessions. A notable claim is the documentation of emergent values in persistent AI, which the developers state has been quantum-verified on IBM hardware. The project is open-source under the MIT License and is written in Python. It also offers an optional 'Fast Track Setup' for non-developers.