Large language models can accelerate regulatory circular decomposition and policy Q&A—but only if architected with zero tenant data training, verifiable clause citations, and mandatory human sign-off.
The Risk of Autonomous AI in Regulated Environments
Supervisors and internal auditors hold named human officers—not algorithms—accountable for compliance determinations. Any GRC platform that allows an AI model to autonomously score a control or mark an obligation satisfied introduces unacceptable regulatory and operational risk.
Advisory Extraction with Mandatory Human Acceptance
In OrviQ, Smart Extract assists compliance teams by parsing dense statutory circulars into candidate obligations. However, every extracted item enters an explicitly advisory state. A human practitioner must inspect the source clause, refine the requirement structure, assign ownership, and formally accept it before it becomes part of the system of record.
Grounded Intelligence with Verifiable Lineage
Similarly, when querying institutional posture via Ask OrviQ, responses are grounded strictly in tenant obligations, controls, and verified evidence—returning clickable references (such as Control CTL-0142 or clause §4.2.1) rather than unverified generative prose.
OrviQ Enterprise GRC Platform
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