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Agent Action Aligner（A3）

Endpoint AI Governance System

For chat clients, IDE agents, CLI tools, and local models on employee endpoints—discover AI assets, protect sensitive outbound data, and assess high-risk agent actions so organizations can keep agent behavior within policy.

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AI app fingerprints

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sensitive data protection types

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behavioral risk detections

Introduction

Hold the line on agent behavior,
controlexecution risk

AI is spreading across desktops and engineering environments. Conversational apps, coding assistants, and automation agents improve productivity but introduce data exfiltration, privilege abuse, and shadow AI that bypasses traditional controls.

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From endpoint AI discovery to closed-loop behavior governance

The overview dashboard connects endpoint AI ingestion, on-device AgentGuard analysis, and policy remediation—plus policy versions, dual-track logs, appeals review, and tuning in one protection-at-a-glance view.

Risk protection for enterprise endpoint AI.
App onboarding and audit—fully controllable and traceable.

Endpoint onboarding

Build an enterprise AI asset inventory

Deploy AgentGuard on employee endpoints, register devices, bind members, and scan for AI tools to understand devices, people, and assets under management.

  • Onboard via registration codes with member and device identity
  • Scan desktop assistants, CLI agents, IDE extensions, and local models on demand or on schedule
  • Searchable inventory by app, member, and device with heartbeat online status
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Policy setup

Define behavior-control rules

Configure agent behavior policies around business requirements—tool scope, risk criteria, and actions—and validate them before they go live.

  • Set rules, priority, and scope by department, user, AI app, and data class
  • Maintain allow/deny lists for AI apps and configure privacy and behavior-risk actions
  • Sandbox sample runs to verify hits, then roll out versioned policies with hot update
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Risk analysis

Detect sensitive content and high-risk intent

Identify AI apps and split traffic, extract the current-turn input, and assess imminent agent actions with user intent, targets, and context—separating data leakage from dangerous execution.

  • Layered detection: regex generalization, on-device semantics, scenario MoE, and platform policies
  • Focus on the current-turn input, with history as supporting context
  • Flag privilege abuse, destructive ops, and composite behavior risks
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Endpoint remediation

Enforce protection before actions land

Apply policy outcomes on the endpoint—block before sensitive data is sent or risky actions execute, or observe-only when appropriate for the business.

  • Block policy-hit requests or actions; let normal work continue
  • Ban disallowed desktop AI apps, with restore supported
  • Desktop alerts explain blocks; offline use keeps cached policy
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Audit & tuning

Evidence and continuous improvement

Aggregate AI usage, sensitive outbound events, and agent behavior into searchable logs and risk views—appeals, reviews, and reports support compliance and policy iteration.

  • Separate privacy and behavior logs linked to member, device, app, policy, and outcome
  • Review false-positive appeals; feed approved exemptions into policy tuning
  • Risk rollups by time, department, and AI app for compliance reporting
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Connect endpoint AI usage with risk governance
Keep data and behavior controllable end to end

Financial sensitive data protection

For research, risk, support, and operations teams—detect unpublished results, M&A details, customer or account data, and contract terms before they reach external models. Turn-level detection and scenario experts reduce chat and file-upload leakage, with audit evidence retained.

Research draft

Industry research report (sample)

Current-turn input

Analyze unpublished earnings forecast [sample]

Turn extraction · finance expert

Detection result

Unpublished earnings

Sensitive financial content detected

Hit

Block and retain

Stop sensitive outbound content

Audit record

Detection and block logged

Input capture
Risk decision
Audit trail

Sample data

A governance loop
that keeps AI continuously trustworthy

Plan AI

A risk governance loop across the full AI lifecycle—linking compliance registration, asset discovery, evaluation, control, and audit end to end to help enterprises operationalize AI planning systematically and avoid fragmented responses.

Discover AI

Make enterprise AI assets visible and controllable. Automatically inventory models, agents, skills, MCPs, and more to surface risk exposure and inform governance decisions.

Evaluate AI

Deep pre-launch risk evaluation to keep hazards out of production. Systematically assess agents, skills, and supply chains for hallucination, overreach, and privacy risks.

Protect AI

Security across agent runtime and multimodal content. Real-time checks and intervention on inputs and outputs, plus AIGC authenticity, tamper detection, provenance, and copyright risk review—balancing speed and governance.

Audit AI

Adaptive compliance for regulatory needs. Full-chain behavioral logging, iterative policy tuning, and support for registration requirements—reducing ongoing compliance cost.

Make every endpoint AI call controllable and traceable

Whether you need AI asset visibility, sensitive data protection, dev-agent controls, or Shadow AI governance—we can help you deploy practical endpoint agent governance.

TRUSTWORTHY AI WITH LEADING PARTNERS

GenTel

Contact us

HQ: 17F, Building 2, Torch Innovation Center, 239 Jucai Rd, Binjiang, Hangzhou

Office: 201, Block X3, 18 Longyao Rd, Xuhui, Shanghai

18F, Huaxin Center, 68 Pazhou Ave, Haizhu, Guangzhou

Partnerships: info@gentel.com

Phone: 400-600-2030

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