AgentRx
AI Auto-Heal Testing for Enterprise Test Automation
Every release breaks something in your automation. AgentRx repairs broken locators in real time, even through major UI redesigns, keeping your CI pipelines uninterrupted. It’s proven to auto-heal ~95% of failures across 3,000,000+ executions.
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Modern Applications Don’t Break Tests. Redesigns Do.
Most self-healing tools are designed to tolerate minor DOM noise. They survive small attribute changes. They fail when layouts shift, components are restructured, or user flows change.
That is the point where maintenance becomes unavoidable and pipelines stall.
AgentRx is built for this exact failure mode: large-scale interface change under continuous delivery pressure.
Meet AgentRx
AI Self-Healing Test Automation for Modern Enterprises
AgentRx is a self-healing engine for your automated UI tests that detects interface changes during execution and rewrites broken locators automatically. By adapting to shifting layouts, labels, attributes, and dynamic UI elements, it maintains end-to-end automation stability across releases without requiring manual script updates.
AgentRx heals based on user intent rather than static selectors. As long as the target element exists in any recognizable form, it identifies it and restores execution. This applies even when the element’s structure, label, or visual appearance changes significantly between builds.
Request Free TrialAgentRx Core Capabilities for AI Auto-Healing Testing at Scale
Multimodal Vision-Language Intelligence
Powered by a Vision-Language Model (VLM), AgentRx understands both your code structure and on-screen visuals. This dual perspective enables accurate element recognition and robust healing when UI structures shift
Instant Locator Rewrites
When interfaces update, AgentRx detects element changes on the fly and rewrites locator logic in milliseconds – before failures surface. Your regression runs continue without downstream pipeline disruption.
Zero Manual Intervention
In the vast majority of cases, your broken locators are healed automatically. No re-recording, no repetitive edits, and no emergency fixes during release week. You stay focused on feature delivery rather than test maintenance.
Cross-Browser Stability
Your automation remains consistent across Chrome, Firefox, Safari, Edge, and other environments. AgentRx adjusts to browser-specific rendering differences, reducing flakiness and improving reliability.
Fix Breaks Before They Block Releases with AI Auto-Heal Testing
Real interfaces change constantly. AgentRx handles it all.
Attribute Tweaks
IDs and placeholders change. You stay anchored to stable text, tags, and CSS context.
Label Changes
“Login” becomes “Sign In.” Your flows continue without rework.
Layout Shifts
Redesigns move elements across the page. Your targets are rediscovered automatically.
Dynamic IDs
Frameworks generate new IDs every run. You align to persistent patterns instead.
Copy & Style Overhauls
Labels and classes get rewritten. Your regression coverage holds.
Localization Updates
UI text changes across languages. Your test logic remains intact.
Icon-Only Controls
Text disappears in favor of icons. You still resolve the correct control.
Unexpected Pop-ups
Overlays hijack interaction paths. You clear them without blocking execution.
How CoTester AgentRx Auto Healing Works in Production
AgentRx operates as CoTester’s auto-healing execution layer, activating during your test runs to recover broken locators in real time.
Works with CoTester Test Generation
AgentRx attaches to the tests you create from stories, specifications, and recorded flows inside CoTester and protects them from UI breakage during execution.
Uses the Same Vision-Language Intelligence
Integrate your tools, CI/CD systems, or analytics platforms with TestGrid’s open APIs and AI Agents to create seamless enterprise workflows.
Runs Inside CoTester’s Enterprise Deployment
Expand your portfolio and revenue by offering TestGrid’s AI-powered testing solutions to your enterprise clients with full sales and technical enablement support.
Real Impact for Engineering and QA Teams
~95% of locator failures healed automatically
Validated across 3,000,000+ test executions
Material reduction in test maintenance workload
2 to 3× faster regression cycles with materially lower maintenance overhead
QA effort refocused from script repair to coverage expansion and defect discovery
Transform Fragile UI Automation into a Stable, AI Self-Healing System
Replace brittle locator dependency with resilient, runtime healing at enterprise scale with AgentRx. Ship faster.
See CoTester AgentRx auto healing in action.
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Frequently Asked Questions (FAQs)
01
How are AI self-healing test automation platforms different from traditional automation tools?
Traditional automation tools rely on static locators that break whenever the UI changes. AI self-healing test automation platforms use visual, structural, and contextual signals to dynamically rediscover elements during runtime. This removes the constant cycle of script repair and significantly reduces regression instability.
01
How are AI self-healing test automation platforms different from traditional automation tools?
Traditional automation tools rely on static locators that break whenever the UI changes. AI self-healing test automation platforms use visual, structural, and contextual signals to dynamically rediscover elements during runtime. This removes the constant cycle of script repair and significantly reduces regression instability.
02
How is CoTester AgentRx auto healing different from other self-healing tools?
CoTester AgentRx auto healing operates at the execution layer using a multimodal Vision-Language Model. It understands both DOM structure and on-screen visuals, allowing it to recover from major redesigns, not just minor attribute changes. It also runs entirely within CoTester’s private cloud and on-prem deployments, preserving enterprise control and ownership.
02
How is CoTester AgentRx auto healing different from other self-healing tools?
CoTester AgentRx auto healing operates at the execution layer using a multimodal Vision-Language Model. It understands both DOM structure and on-screen visuals, allowing it to recover from major redesigns, not just minor attribute changes. It also runs entirely within CoTester’s private cloud and on-prem deployments, preserving enterprise control and ownership.
03
What does AI auto-healing mean in real-world test execution?
AI auto-healing means your tests recover automatically during execution without manual script updates. If an element changes due to redesigns, copy updates, layout shifts, or dynamic IDs, the system heals the locator instantly so your regression pipeline continues without interruption.
03
What does AI auto-healing mean in real-world test execution?
AI auto-healing means your tests recover automatically during execution without manual script updates. If an element changes due to redesigns, copy updates, layout shifts, or dynamic IDs, the system heals the locator instantly so your regression pipeline continues without interruption.
04
Does AI auto-healing introduce risk or reduce test reliability?
When implemented at the execution layer with proper safeguards, AI auto-healing increases reliability rather than reducing it. CoTester AgentRx auto healing applies runtime recovery using multiple validation signals and supports controlled fallback for rare edge cases where full context is removed.
04
Does AI auto-healing introduce risk or reduce test reliability?
When implemented at the execution layer with proper safeguards, AI auto-healing increases reliability rather than reducing it. CoTester AgentRx auto healing applies runtime recovery using multiple validation signals and supports controlled fallback for rare edge cases where full context is removed.
05
What is AI self-healing test automation?
AI self-healing for test automation refers to the use of machine learning and visual intelligence to automatically detect UI changes and repair broken locators during execution. Instead of failing when elements move, rename, or change structure, the system adapts in real time to maintain test continuity.
05
What is AI self-healing test automation?
AI self-healing for test automation refers to the use of machine learning and visual intelligence to automatically detect UI changes and repair broken locators during execution. Instead of failing when elements move, rename, or change structure, the system adapts in real time to maintain test continuity.