SARC: A Governance-by-Architecture Framework for Agentic AI Systems

• URL: http://arxiv.org/abs/2605.07728v1
• Date: Fri, 08 May 2026 13:34:36 GMT
• Title: SARC: A Governance-by-Architecture Framework for Agentic AI Systems
• Abstract summary: Agentic AI systems increasingly act through tools, sub-agents, and external services, but governance controls are still commonly attached to prompts, dashboards, or post-hoc documentation.<n>We introduce SARC, a runtime governance architecture for tool-using agents that treats constraints as first-class specification objects alongside state, action space, and reward.<n>SARC executes zero hard-constraint violations under exact predicates; its declared PAA throttling response reduces soft-window overages by 89.5% relative to policy-as-code-only.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Agentic AI systems increasingly act through tools, sub-agents, and external services, but governance controls are still commonly attached to prompts, dashboards, or post-hoc documentation. This creates a structural mismatch in regulated settings: obligations that must constrain execution are often evaluated only after execution has occurred. We introduce SARC, a runtime governance architecture for tool-using agents that treats constraints as first-class specification objects alongside state, action space, and reward. A SARC specification declares each constraint's source, class, predicate, verification point, response protocol, and operating point, and compiles these into four enforcement sites in the agent loop: a Pre-Action Gate, an Action-Time Monitor, a Post-Action Auditor, and an Escalation Router. We formalize the minimal invariants required for specification-trace correspondence, show why finite reward penalties do not generally substitute for hard runtime constraints, and extend the architecture to multi-agent workflows through constraint propagation, authority intersection, and attribution-preserving trace trees. We implement a prototype audit checker and report a reproducible synthetic evaluation over 50 seeds comparing SARC against post-hoc audit, output filtering, workflow rules, and policy-as-code-only baselines on a procurement task. SARC executes zero hard-constraint violations under exact predicates; its declared PAA throttling response reduces soft-window overages by 89.5% relative to policy-as-code-only. Predicate-noise and enforcement-failure sweeps are consistent with the claim that residual hard violations under SARC scale with enforcement-stack error rather than environmental violation opportunity. SARC provides the architectural substrate through which obligations can be made executable, inspectable, and auditable at runtime.

Related papers

• $Z^2$-ACT: End-to-End Verifiable Agentic Intent Control for Open 6G RAN [43.15181031994434]
  We propose a zero-knowledge auditable control and zero-trust verifiable agentic intent architecture.<n>A live large language model is used in the non-real-time path to translate operator intents into Intent Contracts.<n>Results indicate improved actuation filtering and attack resilience at modest latency and signaling cost.
  arXiv  Detail & Related papers  (2026-08-21T12:44:03Z)
• Formal Verification of Agentic Systems over Operational Data [59.98246281888422]
  Agentic systems driven by large language models (LLMs) are increasingly deployed in real-world where they act on persistent operational data.<n>Existing approaches do not provide such system-level guarantees.<n>We study here the verification of agentic systems comprising a single LLM and a tool orchestration harness over relational operational data.
  arXiv  Detail & Related papers  (2026-08-04T13:01:30Z)
• PhyAgentOS: A Self-Evolving Operating System for Embodied Agents with Decoupled Cognitive Planning and Physical Execution [49.776611937968]
  We present PhyAgentOS, a foundation delivering scheduling, verification, memory, benchmarking, and safety as system-level services.<n>Its Session-Centered treats a session, not an action, as the minimum unit of scheduling, compatibility, supervised execution, evidence collection, and acceptance.<n>SessionVerifier distinguishes execution termination from semantic task completion via evidence-grounded verdicts of success, failure, or replan.<n> Benchmarking reuses the deployment session and verification path, so results trace to real execution.
  arXiv  Detail & Related papers  (2026-07-18T04:46:53Z)
• Constraint Tax in Open-Weight LLMs: An Empirical Study of Tool Calling Suppression Under Structured Output Constraints [37.92327096151557]
  This paper reports reproducible phenomenon observed in a production Agent system.<n>Multiple open-weight models cease invoking tools despite maintaining high schema compliance.<n>We propose Transparent Two-Execution, an inference-time strategy that decouples tool execution from schema-constrained response generation.
  arXiv  Detail & Related papers  (2026-06-24T09:14:18Z)
• An Organization-Scoped LLM Agent Runtime Architecture for Regulated Cybersecurity Operations [0.3013679260442808]
  Regulated cybersecurity lack a runtime substrate that enforces organization-level scope.<n>Recent large language model (LLM) agent systems report strong results on isolated cybersecurity tasks.<n>This paper proposes an organization-scoped agent runtime architecture for financial cybersecurity.
  arXiv  Detail & Related papers  (2026-05-28T21:51:38Z)
• Citation-Closure Retrieval and Per-Rule Attribution for Real-World Regulatory Compliance Question Answering [54.97384993676565]
  We formalize Regulatory Compliance QA with RegOps-Bench, a novel benchmark featuring an Operational Knowledge Graph derived from complex national R&D regulations.<n>RefWalk traverses cross-document citations, fuses multi-view candidates via max-based aggregation, and enforces per-rule attribution to explicitly map claims to sources.
  arXiv  Detail & Related papers  (2026-05-28T10:38:38Z)
• Governance by Construction for Generalist Agents [7.48004748585128]
  This demo presents CUGA's policy system, a modular policy-as-code layer that composes with a generalist agent to deliver predictable, auditable, and compliance-aware behavior.<n>We present a governance architecture that enforces policy interventions at every critical stage of execution.
  arXiv  Detail & Related papers  (2026-05-20T08:13:16Z)
• Securing the Agent: Vendor-Neutral, Multitenant Enterprise Retrieval and Tool Use [0.0]
  We introduce a layered isolation architecture combining policy-aware ingestion, retrieval-time gating, and shared inference.<n>This approach centralizes security-critical operations--tool execution authorization, state isolation, and policy enforcement--on the server.<n>We evaluate it empirically and show that ABAC gating eliminates cross-tenant leakage while introducing negligible overhead.
  arXiv  Detail & Related papers  (2026-05-06T17:59:21Z)
• IMPACT-CYCLE: A Contract-Based Multi-Agent System for Claim-Level Supervisory Correction of Long-Video Semantic Memory [73.22944697933603]
  Existing pipelines produce opaque, end-to-end outputs that expose no intermediate state for inspection.<n>We present IMPACT-Cycle, a supervisory multi-agent system that reformulates long-video understanding as a multimodal iterative claim-level maintenance.
  arXiv  Detail & Related papers  (2026-04-22T03:03:33Z)
• KAIJU: An Executive Kernel for Intent-Gated Execution of LLM Agents [5.931389072124715]
  Tool-calling autonomous agents based on large language models using ReAct exhibit three limitations.<n>Recent work moves towards separating planning from execution but in each case model remains coupled to the execution mechanics.<n>We introduce a system-level abstraction for LLM agents which decouples the execution agent from the reasoning layer.
  arXiv  Detail & Related papers  (2026-03-31T21:38:28Z)
• Dynamic analysis enhances issue resolution [53.50448142467294]
  DAIRA (Dynamic Analysis-enhanced Issue Resolution Agent) is an automated repair framework that embeds dynamic analysis into the agent's reasoning cycle.<n> Driven by a Test Tracing-Driven methodology, DAIRA utilizes lightweight monitors to extract critical runtime data.<n>When powered by Gemini 3 Flash Preview, DAIRA establishes a new state-of-the-art (SOTA) performance, achieving a 79.4% resolution rate on the SWE-bench Verified dataset.
  arXiv  Detail & Related papers  (2026-03-23T14:48:54Z)
• A Trace-Based Assurance Framework for Agentic AI Orchestration: Contracts, Testing, and Governance [0.22940141855172028]
  This paper presents an assurance framework for Agentic AI systems using Large Language Models (LLMs)<n>Executions are instrumented as Message-Action Traces (MAT) with explicit step and trace contracts.<n>The framework includes stress testing, formulated as a budgeted counterexample search over bounded perturbations.
  arXiv  Detail & Related papers  (2026-03-18T10:23:48Z)
• Cryptographic Runtime Governance for Autonomous AI Systems: The Aegis Architecture for Verifiable Policy Enforcement [0.0]
  This paper presents Aegis, a runtime governance architecture for autonomous AI systems.<n>Aegis treats policy and legal constraints as execution conditions rather than advisory principles.
  arXiv  Detail & Related papers  (2026-03-15T04:04:57Z)
• ESAA-Security: An Event-Sourced, Verifiable Architecture for Agent-Assisted Security Audits of AI-Generated Code [0.0]
  This paper presents ESAA-Security, a domain-specific framework for agent-assisted security auditing of software repositories.<n>The framework produces structured check results, vulnerability inventories, severity classifications, risk, remediation guidance, executive summaries, and a final markdown/JSON audit report.
  arXiv  Detail & Related papers  (2026-03-06T15:15:26Z)
• Robust and Efficient Tool Orchestration via Layered Execution Structures with Reflective Correction [55.13278005189741]
  We model tool orchestration as learning a layered execution structure that captures high-level tool dependencies.<n>We introduce a schema-aware reflective correction mechanism that detects and repairs errors locally.<n>This design confines errors to individual tool calls and avoids re-planning entire execution trajectories.
  arXiv  Detail & Related papers  (2026-02-21T22:20:01Z)
• Analyzing and Internalizing Complex Policy Documents for LLM Agents [53.14898416858099]
  Large Language Model (LLM)-based agentic systems rely on in-context policy documents encoding diverse business rules.<n>This motivates developing internalization methods that embed policy documents into model priors while preserving performance.<n>We introduce CC-Gen, an agentic benchmark generator with Controllable Complexity across four levels.
  arXiv  Detail & Related papers  (2025-10-13T16:30:07Z)
• SOPBench: Evaluating Language Agents at Following Standard Operating Procedures and Constraints [59.645885492637845]
  SOPBench is an evaluation pipeline that transforms each service-specific SOP code program into a directed graph of executable functions.<n>Our approach transforms each service-specific SOP code program into a directed graph of executable functions and requires agents to call these functions based on natural language SOP descriptions.<n>We evaluate 18 leading models, and results show the task is challenging even for top-tier models.
  arXiv  Detail & Related papers  (2025-03-11T17:53:02Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.