Company • Kayalogy

Swiss-developed medical AI, built for earlier detection.

Kayalogy develops browser-native medical imaging AI for early cancer detection, with a focus on privacy-first workflows, structured evaluation, and a scalable pathway toward clinical deployment.

Focus
Medical Imaging AI
Early detection workflows
Delivery
Browser-native
No local installation
Governance
Privacy-first
Controlled handling principles
Development
Quality-aligned
Structured SaMD pathway
Kayalogy mission and company direction

A focused mission

Kayalogy is built around a simple objective: to make advanced medical imaging AI more accessible for earlier cancer detection. We focus on practical deployment, structured validation, and product discipline rather than research-style complexity alone.

  • Early detection as the central product objective
  • Designed for clinical relevance and measurable performance
  • Built in Switzerland with a long-term MedTech mindset
Browser-native platform architecture

A browser-native platform

The platform is designed for direct access through the browser, reducing operational friction and supporting scalable deployment across institutions. This enables a unified product experience without relying on local installation workflows.

  • Browser-based delivery for simpler access and rollout
  • Platform structure designed for multiple imaging workflows
  • Scalable architecture for institutional and B2B use
Privacy and governance principles

Privacy and governance by design

Sensitive medical data requires strict handling. Kayalogy is developed with privacy-first principles, controlled access logic, and clear governance expectations to support institutional trust and responsible platform operation.

  • Privacy-first handling principles for medical imaging data
  • Access-control logic and deletion-oriented governance thinking
  • Designed for Swiss and applicable European data protection expectations
Validation and collaboration model

Built for validation and collaboration

Kayalogy is developed with a structured path toward evaluation in real-world settings. The company works toward collaboration with clinical, academic, and industry stakeholders to support validation, documentation, and future deployment readiness.

  • Structured support for evaluation and validation programs
  • Traceable outputs and measurable performance reporting
  • Development aligned with future regulatory and quality expectations