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Blog Topic
Compliance and governance for agent operations.
24 metadata-ranked posts in this topic
Ranked for relevance, freshness, and usefulness so readers can find the strongest Armalo posts inside this topic quickly.
Multi-agent swarms amplify what is good and bad about individual agents simultaneously. Getting the intelligence without the risk requires governance architecture designed for distributed autonomous behavior, not retrofitted from single-agent controls.
AI governance regulation is arriving faster than most enterprise teams expect, and the compliance requirements for autonomous agent deployments are unlike anything in the existing AI compliance playbook. Preparation time is shorter than it looks.
The definitive B2B procurement framework for CIOs and CISOs buying AI agents — covering EU AI Act compliance, 25 RFP questions with scoring rubrics, 15 must-have contract clauses, a 10-metric KPI framework, and a red team protocol that separates production-ready agents from vendor theater.
Mapping AI Agent Controls to NIST AI RMF and the EU AI Act for compliance officer: how to crosswalk internal controls to regulator frameworks. This post centers the compliance theater — mappings without evidence failure mode and explains why AI agents need trust infrastructure to carry real staying power.
Translate security controls demand high-fidelity evidence and override history into practical Agent Trust controls for cybersecurity teams.
A layered explanation of the AI trust infrastructure stack, including identity, behavioral contracts, evaluation, scoring, audit trails, and consequence design.
Translate strict quality and mission-assurance governance requirements into practical Agent Trust controls for aerospace teams.
The AI infrastructure stack has a gap in it. We have model providers, prompt management, LLM observability, fine-tuning. What we don't have is the layer that specifies what an agent is supposed to do — in machine-readable form, independently of how it's implemented.
Three Controls Your Compliance Team Will Demand for fintech compliance: the minimum three controls to satisfy regulator + reduce real risk. This post centers the over-controlling the audited path, under-controlling the agent path failure mode and explains why AI agents need trust infrastructure to carry real staying power.
Translate safety and product quality accountability with auditable decisions into practical Agent Trust controls for automotive teams.
HIPAA, Clinical Decision Support, and Behavioral Proof for healthcare CIO: HIPAA + clinical-decision-support controls for agents. This post centers the compliance theater that doesn't survive an audit failure mode and explains why AI agents need trust infrastructure to carry real staying power.
How rights-ops teams operationalize audit-ready trust controls.
How assessment-integrity teams operationalize audit-ready trust controls.
Translate consumer policy adherence with transparent exception flows into practical Agent Trust controls for retail teams.
How gaming-liveops teams operationalize audit-ready trust controls.
How sustainability teams operationalize audit-ready trust controls.
Translate tenant communication and contractual policy consistency into practical Agent Trust controls for real-estate teams.
How fleet-ops teams operationalize audit-ready trust controls.
Translate GxP-compatible evidence and strict change control into practical Agent Trust controls for pharma teams.
Translate public accountability and auditable chain-of-custody requirements into practical Agent Trust controls for public-sector teams.
Translate food safety and traceability obligations across supply chain into practical Agent Trust controls for agriculture teams.
Translate service entitlement policy conformance and transparency into practical Agent Trust controls for travel teams.
How creator-ops teams operationalize audit-ready trust controls.
Translate safety-first governance and operator override visibility into practical Agent Trust controls for manufacturing teams.
Safety Research
A public roadmap for calibrated workspace research across eight evidence gates: calibration, behavior, specificity, entanglement, sparse features, agent telemetry, self-monitoring, and adversarial robustness.