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Evidence record 7062 · automatically gathered

Governed Memory: A Production Architecture for Multi-Agent Workflows

Enterprise AI deploys dozens of autonomous agent nodes across workflows, each acting on the same entities with no shared memory and no common governance. We identify five structural challenges arising from this memory governance gap: memory silos across agent workflows; governance fragmentation across teams and tools; unstructured memories unusable by downstream systems; redundant context delivery in autonomous multi-step executions; and silent quality degradation without feedback loops. We pres

Record details

Published: 18 March 2026
Source: arXiv
Category: Research
Topics: Regulation · Agents & autonomy
Retrieved: 14 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

Shared topic: Regulation · Shared topic: Agents & autonomy

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Shared topic: Regulation · Shared topic: Agents & autonomy

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Shared topic: Regulation · Shared topic: Agents & autonomy

MemArchitect: A Policy Driven Memory Governance Layer

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Shared topic: Regulation · Shared topic: Agents & autonomy

Soft-Label Governance for Distributional Safety in Multi-Agent Systems

arXiv · 19 March 2026

Shared topic: Regulation · Shared topic: Agents & autonomy

Agent Control Protocol: Admission Control for Agent Actions

arXiv · 19 March 2026

Shared topic: Regulation · Shared topic: Agents & autonomy

I Can't Believe It's Corrupt: Evaluating Corruption in Multi-Agent Governance Systems

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How to cite this record

ethics.ai (18 March 2026), “Governed Memory: A Production Architecture for Multi-Agent Workflows,” evidence record 7062, https://ethics.ai/record/7062 (originally published by arXiv).

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