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International Journal of Advanced Artificial Intelligence Research

Open Access Peer Review International
Open Access

Human-in-the-Loop Control Planes for Cortex Agents: Policy-Driven Escalation, Approval, and Evidence Capture

DOI https://doi.org/10.55640/ijaair-v03i09-05
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Sashank Siwakoti 1 , Bhaskar Chaganti 1 ,
4 Independent Researcher, USA
4 Independent Researcher, USA

Abstract

Purpose. Enterprise agents can accelerate anomaly triage and regulated reporting, yet ordinary access control, prompt instructions, and post-hoc traces do not define a complete authorization contract for consequential actions. This study develops PAVE-CP, a vendor-neutral control plane that determines when an agent must escalate, which evidence must accompany the request, who may approve, and how the resulting decision is enforced and recorded.

Design/methodology/approach. Following design-science research, requirements are derived from human–automation research, security principles, policy-as-code, provenance, AI-governance sources, recent agent-authorization work, and documented Cortex Agents interfaces. The artifact comprises a canonical action envelope, policy decision point, graded evidence model, approval broker, exact-action tokens, governed execution gate, postcondition verification, and a tamper-evident event ledger. Evaluation combines one million randomized policy-state checks, 20,000 end-to-end authorization checks, seven seeded mutations, and a reproducible discrete-event simulation of one million proposed actions.

Findings. The reference controller produced no structural mismatch in the exercised randomized and end-to-end state spaces and detected all seven seeded mutations. Under the stated synthetic assumptions, PAVE-CP routed 16.54% of proposals to review, preserved 81.78% bounded autonomy, and produced 0.36 modeled high-impact unsafe commits per 10,000 proposals, compared with 129.79 for role-based autonomy and 14.92 for blanket human review. Median latency was 2.34 seconds, while the approval-bound 95th percentile remained 237.10 seconds.

Originality, implications, and limits. The contribution is an externally enforceable commit protocol, not another prompt guardrail or observability dashboard. It binds policy, evidence, human authority, exact parameters, freshness, separation of duties, execution, and audit evidence into one verifiable control object. The Cortex mapping shows how rapid read-only investigation and drafting can coexist with explicit authorization for regulated publication and high-impact state change. Quantitative results are synthetic design-science evidence, not production telemetry or a compliance claim.

Keywords

AI agents, Human-in-the-loop, Runtime authorization, Control plane, Policy-as-code, Evidence capture, Approval workflow, Auditability, Snowflake Cortex Agents, Regulated reporting, Anomaly triage

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