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A Blockchain-Monitored Agentic AI Architecture for Trusted Perception-Reasoning-Action Pipelines

Artificial Intelligence 2026-03-19 v1 Multiagent Systems

Abstract

The application of agentic AI systems in autonomous decision-making is growing in the areas of healthcare, smart cities, digital forensics, and supply chain management. Even though these systems are flexible and offer real-time reasoning, they also raise concerns of trust and oversight, and integrity of the information and activities upon which they are founded. The paper suggests a single architecture model comprising of LangChain-based multi-agent system with a permissioned blockchain to guarantee constant monitoring, policy enforcement, and immutable auditability of agentic action. The framework relates the perception conceptualization-action cycle to a blockchain layer of governance that verifies the inputs, evaluates recommended actions, and documents the outcomes of the execution. A Hyperledger Fabric-based system, action executors MCP-integrated, and LangChain agent are introduced and experiments of smart inventory management, traffic-signal control, and healthcare monitoring are done. The results suggest that blockchain-security verification is efficient in preventing unauthorized practices, offers traceability throughout the whole decision-making process, and maintains operational latency within reasonable ranges. The suggested framework provides a universal system of implementing high-impact agentic AI applications that are autonomous yet responsible.

Keywords

Cite

@article{arxiv.2512.20985,
  title  = {A Blockchain-Monitored Agentic AI Architecture for Trusted Perception-Reasoning-Action Pipelines},
  author = {Salman Jan and Hassan Ali Razzaqi and Ali Akarma and Mohammad Riyaz Belgaum},
  journal= {arXiv preprint arXiv:2512.20985},
  year   = {2026}
}

Comments

This paper was presented at the IEEE International Conference on Computing and Applications (ICCA 2025), Bahrain

R2 v1 2026-07-01T08:39:37.902Z