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AI-Augmented DevSecOps Toolchains for Compliance-Critical Cloud Applications in Healthcare and Finance

Author(s) Sai Nitesh Palamakula
Country United States
Abstract Cloud applications in healthcare and finance must comply with stringent regulations such as HIPAA, PCI-DSS, and SOC 2. Traditional DevSecOps pipelines rely on manual policy checks and static scanners, which often fail to detect emerging vulnerabilities and compliance drift in real time. This paper introduces an AI-augmented DevSecOps toolchain that embeds autonomous agents throughout the CI/CD workflow to dynamically enforce regulatory controls. The proposed system integrates static code analysis, container scanning, and infrastructure-as-code validation with machine learning models trained to recognize non-compliant patterns in code and configuration. The architecture supports continuous compliance enforcement, reduces manual overhead, and improves audit readiness across regulated cloud environments. This paper delves into the design, implementation of this framework, highlighting its applicability to healthcare and financial workloads.
Keywords DevSecOps, Artificial Intelligence, Compliance, Security, AI Agents, CI/CD, Healthcare, Finance, Retrieval-Augmented Generation
Field Engineering
Published In Volume 6, Issue 7, July 2025
Published On 2025-07-25
Cite This AI-Augmented DevSecOps Toolchains for Compliance-Critical Cloud Applications in Healthcare and Finance - Sai Nitesh Palamakula - IJLRP Volume 6, Issue 7, July 2025. DOI 10.70528/IJLRP.v6.i7.1686
DOI https://doi.org/10.70528/IJLRP.v6.i7.1686
Short DOI https://doi.org/g9v44r

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