A Blockchain-Monitored Agentic AI Architecture for Trusted Perception-Reasoning-Action Pipelines
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866908897974943744 |
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| author | Jan, Salman Razzaqi, Hassan Ali Akarma, Ali Belgaum, Mohammad Riyaz |
| author_facet | Jan, Salman Razzaqi, Hassan Ali Akarma, Ali Belgaum, Mohammad Riyaz |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_20985 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Blockchain-Monitored Agentic AI Architecture for Trusted Perception-Reasoning-Action Pipelines Jan, Salman Razzaqi, Hassan Ali Akarma, Ali Belgaum, Mohammad Riyaz Artificial Intelligence Multiagent Systems 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. |
| title | A Blockchain-Monitored Agentic AI Architecture for Trusted Perception-Reasoning-Action Pipelines |
| topic | Artificial Intelligence Multiagent Systems |
| url | https://arxiv.org/abs/2512.20985 |