VERITARCH: A Governance Architecture for Multi-Agent AI Systems Based on Decentralized Exchange Protocol Principles

This technical report presents the system master specification (VAS-MASTER-001) for the VERITARCH Agent System (VAS), a governance architecture designed for multi-agent AI organizations operating under single-human oversight. The system is composed of 39 AI agents organized into 8 departments across a four-layer organizational hierarchy, where decision-making authority is retained by a single human principal and autonomy is granted to agents only as operational stakes decrease. Structural trustworthiness is pursued not through the assumed reliability of individual agents but through architectural constraints adapted from decentralized exchange protocol (DEP) mechanisms. Five governance principles are embedded into the system design: transparent audit trails, automated governance enforcement, distributed consensus, engineered cognitive diversity, and layered containment. These principles are operationalized through 16 internal regulations comprising approximately 98 articles, which are encoded as self-executing protocols rather than discretionary guidelines. The specification documents an internal checks-and-balances framework constraining the orchestrator agent, an external data acquisition regulation restricting agent access to approved sources, a six-layer technical architecture governing information flow, a three-layer mandatory template system enforcing standardized agent development, a five-stage human-in-the-loop workflow validated across four operational scenarios, and a 22-SPEC development roadmap. This document serves as a companion technical reference to a related governance framework proposal submitted to an academic journal. Full implementation details are provided in the embargoed specification file.