CyberAI develops auditable, deployment-aware cybersecurity and trustworthy AI solutions for cloud, edge, connected systems, SMEs and collaborative European R&D.
CyberAI is structured to move between research questions, prototypes and deployable security modules without inflating claims, headcount or project status.
Telemetry is converted into traceable security context, model-level signals and response-ready evidence.
Assumptions, data lineage, validation boundaries and readiness levels are stated explicitly.
Components can be evaluated independently or integrated into a broader security architecture.
CyberAI can contribute technical work packages, prototype engineering, research validation, SME pilots and cybersecurity evidence architecture.
Threat models for poisoning, adversarial manipulation, privacy leakage and unsafe deployment are converted into measurable control points.
Security telemetry, workload context and edge conditions are joined without assuming unlimited compute or perfect connectivity.
Device telemetry, operational states and anomaly signals are structured into a traceable view suitable for industrial and IoT environments.
Lightweight deployment, understandable evidence and compliance-aware outputs are prioritised for resource-constrained organisations.
Each engagement is framed by the claim being tested, the evidence required, the prototype boundary and the deployment decision it should support.
Define the asset, threat, operational constraint and measurable security objective.
Boundary agreedBuild a focused module or prototype with traceable data and assumptions.
Evidence linkedEvaluate against realistic scenarios, baselines and clearly stated limitations.
Result auditableTranslate the validated mechanism into a deployable technical and organisational path.
Decision readyLightweight monitoring, risk context, incident support and compliance-aware evidence for cloud, edge and connected operations.
Model integrity, poisoning defence, privacy leakage assessment and runtime assurance across the AI lifecycle.
Evidence-aware threat monitoring across distributed workloads, gateways, devices and resource-constrained environments.
CyberAI is led by Dr. Amirhossein Nafei and supported by project-specific researchers, engineers and domain experts selected transparently for each engagement.
Meet the team →The company does not present external collaborators as permanent staff. Roles are disclosed clearly and matched to the actual technical need.
Share the system boundary, project stage and expected output. CyberAI will map the technically credible route.