Validate Safe, Intended Robot
Behavior Before Deployment
Radeis reveals how vulnerabilities and AI model risks could alter what your robot sees, decides, and does. Validate their impact in simulation and prioritize what to fix before release.
Safety Assurance Is Incomplete Without Cyber-Safety Validation
A robot may behave safely under expected conditions, yet respond differently when cyber risk alters its inputs, decision logic, or commands. Traditional assessments identify vulnerabilities. Radeis shows which ones could push robot behavior beyond safe limits.
Manipulated Input
Spoofed sensor, vision, or voice data changes what the robot perceives.
Compromised AI Model or Software
Tampered models, firmware, or middleware alter how the robot interprets inputs and makes decisions.
Compromised Command
Unauthorized or altered commands trigger the wrong movement, route, or task.
AI-Powered Cyber-Safety Validation
Radeis combines AI-agent analysis, attack-driven simulation, and continuous reassessment to validate robot behavior and keep cyber-safety evidence current as risks evolve.
AI agents analyze software, firmware, AI models, dependencies, and configurations to identify risk across the robot stack.
Output: A contextualized view of system, software, and AI risk.
Run the integrated robot software and AI models against curated attack stories to expose whether cyberattacks could trigger unsafe or unintended behavior.
Output: Reproducible evidence of behavior under attack.
Radeis reassesses robot software, AI models, and dependencies as new vulnerabilities and attack intelligence emerge, updating remediation priorities and traceable evidence for review, release, and compliance.
Output: Current risk visibility and compliance-ready evidence as threats evolve.
One Platform for Robot Risk, Safety, and Compliance
Radeis brings component risk, AI model risk, behavior-level safety validation, and compliance readiness into one pre-deployment cyber-safety platform.
- Source Code
- LLM / VLM Endpoints
- Robot URDF
- AI Model / AIBOM
- Firmware / Binaries
- Third-party SBOM
- Third-party HBOM
- Software, firmware, and dependency risk
- Vulnerability and penetration testing
- AI model and AIBOM analysis
- Integrity, provenance, and red teaming for resilience
- Attack-driven simulation
- Validation against intended behavior
- EU Cyber Resilience Act, EU AI Act, and IEC 62443
- Traceable evidence for review and release
- Prioritized Remediation
- Behavior-Level Validation Evidence
- Release and Compliance Readiness
See How Cyber Risk Can Change Robot Behavior
See how publicly disclosed cyber risks could alter intended robot behavior, and how Radeis helps validate the impact before release.
Radeis for Every Team Behind Robot Safety
Shared evidence helps security, engineering, safety, and compliance teams act on the same risk.
Product Security
Prioritize vulnerabilities by their potential impact on robot behavior and safety.
Robotics & AI Engineering
Reproduce attack conditions and see how they affect perception, decisions, and control.
Functional Safety
Assess whether cyber risks could compromise safety functions or invalidate safety assumptions.
Compliance
Build traceable evidence for release and market access, aligned with the EU CRA, EU AI Act, and more.
Why Robot Makers Choose Radeis
Connect Cyber Risk to Physical Safety
Unlike vulnerability scanners that stop at technical findings, Radeis validates whether a weakness could change a critical robot function, behavior, or safety outcome.
Validate Software, AI, and Robot Behavior Together
Assess vulnerable components, manipulated inputs, AI model risks, interfaces, and physical robot responses in one cyber-safety assurance workflow.
Prioritize the Risks That Can Change Critical Behavior
Focus engineering resources on attack paths that could affect perception, decisions, movement, task execution, or other safety-relevant functions.
Produce Traceable Evidence for Assurance and Compliance
Turn system mappings, test scenarios, findings, and behavior-impact results into traceable evidence for remediation, safety reviews, release decisions, and regulatory readiness.
Frequently Asked Questions
Vulnerability scanners stop at technical findings. Radeis goes further and validates whether a weakness could actually change a robot's perception, decisions, movement, or other safety-critical behavior.
No. Radeis reproduces attack conditions in simulation, so teams can validate behavior-level impact before hardware or a final build is available.
Radeis assesses AI models and AIBOMs, firmware and binaries, and third-party SBOM and HBOM data to map the robot's software, AI, and dependency risk.
Radeis produces traceable evidence aligned to CRA, the EU AI Act, and IEC 62443, so findings can carry directly into review and release processes.
Product security, robotics and AI engineering, functional safety, and compliance teams all work from the same assessment evidence.
Ready to Prove Your Robot Is Safe Before It Ships?
Talk to the Radeis team about validating cyber-to-safety risk before deployment.
Contact us