A Conceptual Framework for Multi-Agent AI Quality Control in The Review of Regulated Documents

Abstract

Organizations in pharmaceutical, financial, and other regulated sectors face rising pressure to review large volumes of complex documents against strict and frequently evolving standards, while preserving the traceability needed to defend decisions to auditors and regulators. Large language model (LLM) based automation offers clear efficiency gains, but single-agent deployments raise well-documented concerns about hallucination, opacity, and insufficient auditability, particularly as regulatory

Categories

@article{ominyi2026conceptual,
  title = {{A Conceptual Framework for Multi-Agent AI Quality Control in The Review of Regulated Documents}},
  author = {Michael Ominyi},
  year = {2026},
  month = aug,
  journal = {INTERNATIONAL JOURNAL OF SOCIAL SCIENCES AND MANAGEMENT RESEARCH},
  doi = {10.56201/ijssmr.vol.11no8.2025.pg534.557},
  url = {https://www.semanticscholar.org/paper/ace5593eeb76ba362a29f5c056b74985212eea5b}
}