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Expo Demonstration

Building Safe, Compliant, and Observable Agentic Systems for Generative AI Applications

Yiran Ivy Si

Upper Level Room 29A-D
[ ]
Tue 2 Dec noon PST — 3 p.m. PST

Abstract:

SCOPE: Enterprise Agent Governance Framework

As Large Language Model (LLM) agents are increasingly deployed in mission-critical applications, ensuring their safety, compliance, and observability becomes paramount. We present SCOPE, a comprehensive governance framework designed for regulated environments like banking and healthcare.

The SCOPE acronym represents our five core pillars:

S – Safety (Multi-layer Safety Guardrails)

C – Compliance (Policy-as-Code)

O – Observability (Measurable Observability & Audit Trails)

P – Permissions (Identity-Aware Permissions / IAM)

E – Escalation (Human-in-the-Loop Escalation)

Built on Google's Agent Development Kit (ADK), SCOPE implements a "Defense in Depth" architecture. It combines fast ML-based classification (~50ms) with LLM-based contextual analysis for robust protection. It features Role-Based Access Control (RBAC) baked into the agent's core and enables hot-patching of business rules without code changes.

We demonstrate SCOPE's effectiveness through a live Banking Customer Service Agent that handles account inquiries, transactions, and fraud reports while maintaining compliance with PCI-DSS and SOC2 requirements. The framework is open-source and production-ready, offering a practical blueprint for trustworthy agent deployment.

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