Abstract
Organizations in regulated sectors may face challenges using large-scale, cloud-based artificial intelligence (AI) services because of data sovereignty and compliance mandates. A system may provide a decentralized, agent-aware mesh network that functions as an infrastructure layer to bridge on-premise environments and external AI services. This network can intercept and semantically understand complex agent communications, allowing an active enforcement layer to perform actions such as sanitizing data, pausing high-risk operations for human review, and maintaining a sovereign audit log. This approach can allow organizations to leverage advanced AI reasoning capabilities from external providers while assisting in the maintenance of local control over sensitive data, agent state, and governance, which may help address certain compliance and data residency concerns.
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Recommended Citation
Ojea, Antonio, "Agent-Aware Mesh Network for Hybrid AI Policy Enforcement", Technical Disclosure Commons, ()
https://www.tdcommons.org/dpubs_series/10818