📢 EU AI Liability Directive: Full enforcement by 2026 | US FDA: Final guidance expected Q3 2025. Is your AI system protected?
Medical AI Vulnerabilities are More Dangerous Than You Think
67%
Invisible Attacks, Real Consequences
Medical imaging AI's are vulnerable to imperceptible adversarial attacks that can change diagnoses without visible signs
The average cost of an AI liability claim under new EU and US regulatory frameworks
$5.2M
Unprecedented Liability Exposure
88%
Standard Testing Misses Critical Vulnerabilities
Medical imaging AI systems that pass generic security tests still fail when subjected to domain-specific attack scenarios
AI medical device manufacturers are unprepared for the specialized testing requirements in upcoming regulations
76%
Regulatory Compliance at Risk
"But our systems are internal and isolated. How could they be vulnerable?"
Internal AI systems are still at risk through data pipeline manipulations, unintentional variations in medical images, and third-party components. The EU and US AI Liability Directive doesn't distinguish between intentional attacks and unintentional vulnerabilities—you're liable either way.
The question isn't if you can afford this testing. It's whether you can afford not to have it.
Domain-Specific Adversarial Testing for Healthcare AI
Lensai provides specialized adversarial testing designed specifically for medical imaging AI systems.
Our proprietary MEDROBUST™ framework identifies vulnerabilities that standard compliance testing misses.
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Specialized testing framework designed for medical imaging applications
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Identifies vulnerabilities that standard compliance testing misses
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Architecture-specific testing for CNNs, Vision Transformers, and other models
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Generates comprehensive documentation for regulatory submissions and liability protection
Why Standard Testing Isn't Enough
Medical AI systems face unique challenges that generic security testing cannot address.
Our Proprietary MEDROBUST™ Framework
A comprehensive five-phase approach designed specifically for medical imaging AI systems.
Adversarial Data Generators
Using LensAI servers, generate adversarial data both on-premise and in the cloud
Adversarial attacks affect model predictions (especially in healthcare and vision models)
Patch-level classification of cancer in histopathological images
Continuous Model Observability
Beyond testing, Lensai provides ongoing monitoring to protect your AI systems post-deployment.
Our comprehensive monitoring solution ensures your AI systems remain secure and reliable throughout their operational lifecycle. We provide continuous oversight that integrates with your existing clinical workflows.
Real-time Attack Detection
Lightweight monitoring agents identify adversarial attempts as they occur, providing early warning for potential security threats
Performance Drift Detection
Statistical analysis identifies gradual degradation in model accuracy, preventing "silent failure" scenarios common in medical AI.
Adversarial Sample Database
Constantly updated library of known attack patterns provides protection against emerging threats in the healthcare AI space.
Our Solution
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Test and re-train your models
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Seamless Integration
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Run attack simulations
lensai automatically generates tailored adversarial datasets to expose your model’s weak points. By training on these “worst-case scenarios,” your vision models learn to detect and resist attacks before they happen.
