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

Salman Jan, Hassan Ali Razzaqi, Ali Akarma, Mohammad Riyaz Belgaum
12/24/2025
cs.AIcs.MA

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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.

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Cite this paper

@article{jan2025blockchainmonitored,
  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},
  year   = {2025},
  eprint = {2512.20985},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2512.20985v1}
}

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