Abstract
AI Context Automaton introduces a dual-AI architecture that transforms stateless AI interactions into a stateful, compliance-aware, and environmentally optimised workflow. The system combines a local AI for memory management and compliance enforcement with a cloud-based AI for reasoning, leveraging a markdown-based knowledge base for persistent storage. By offloading memory operations and compliance checks to local devices, the architecture minimises repeated cloud compute cycles, reducing energy consumption, carbon footprint, and operational costs while ensuring adherence to organisational governance standards.
Publication Date
2025-12-18
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Chiesa, David R P, "AI Context Automaton – Extended Architecture for Compliance-Aware Local Memory and Environmental Optimisation", Technical Disclosure Commons, ()
https://www.tdcommons.org/dpubs_series/9082