Codified Data Contracts with LLM-Driven Compliance Enforcement in CI/CD Workflows

Authors: Sai Kishore Chintakindhi

DOI: https://doi.org/10.37082/IJIRMPS.v13.i4.232686

Short DOI: https://doi.org/g9wp43

Country: United States

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Abstract: Generally speaking, this dissertation explores how codified data contracts can be woven into CI/CD workflows, leveraging LLMs to enhance compliance. The main question tackles the difficulty of upholding data governance and accuracy in automated development. A mixed- methods approach combines qualitative and quantitative data on current CI/CD practices, LLM capabilities, and compliance metrics. Findings show that codified data contracts substantially boost compliance by setting clear standards throughout the CI/CD pipeline. This is particularly vital in healthcare, directly affecting patient data security and regulatory adherence, thus building trust and efficiency in health information management systems. The broader impact implies that this framework for LLM-driven compliance can be adapted across healthcare domains, improving data management and patient outcomes. This research highlights the transformative potential of AI in regulatory settings, providing a strategic path towards secure and compliant data practices in healthcare tech's evolving landscape. [citeX] [extractedKnowledgeX]

Keywords: codified data contracts, Continuous Integration (CI), Continuous Deployment (CD), large language models (LLMs), compliance enforcement, data governance, automated software development, data contract testing, schema validation, machine learning (ML) workflows, MLOps and LLMOps, DevSecOps, data privacy, GDPR; CCPA, smart contracts, blockchain, healthcare data security, zero trust architecture, zero knowledge proofs, cross border data management, AI regulatory frameworks, agile software project management.

Paper Id: 232686

Published On: 2025-07-16

Published In: Volume 13, Issue 4, July-August 2025

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