AI Act Compliance by Design

What is AIDOS

AIDOS is Life2Ledger's advanced AI-data observation platform designed to support MedTech AI companies in meeting the strict regulatory requirements imposed by the EU AI Act. By ensuring dataset authenticity, verifiable provenance, GDPR-compliant de-identification, and immutable audit trails, AIDOS enables smaller and mid-sized MedTech developers to achieve enterprise-grade compliance without the associated complexity or cost. The platform strengthens AI governance, improves data integrity, and ensures full traceability across the AI lifecycle.

Through its comprehensive monitoring and archiving capabilities, AIDOS safeguards against corrupted or unwanted synthetic datasets infiltrating data pipelines. With AIDOS, MedTech innovators can accelerate clinical AI development, increase dataset reliability, and demonstrate compliance readiness with confidence—ultimately supporting safer, more trustworthy AI in healthcare settings.

EU AI Act compliance

The AIDOS AI data-observation system is designed for MedTech innovators who need full trust and traceability in their AI development workflows. As almost all medical AI systems fall under the EU AI Act's high-risk category, companies must demonstrate that their AI development processes —including data handling— are reliable, explainable, and auditable.

Although the EU AI Act does not explicitly mandate “authentic and traceable data pipelines”, such capabilities follow directly from the Act's outcome-based requirements for robustness, transparency, auditability, and risk management. In practice, no MedTech AI developer can demonstrate compliance with Articles 9–15 of the Act without being able to verify where data originated and how it has been handled throughout the AI lifecycle. AIDOS provides exactly this: a modular trust technology layer that verifies dataset authenticity, ensures reliable provenance, and delivers immutable, audit-ready records across training, validation, and testing cycles. In addition, AIDOS supports day-to-day clinical use by showing that operational data remains authentic and traceable, and provides a reliable basis for evaluating new algorithm versions, including the comparison of performance between successive model iterations.

AIDOS — AI Act Compliance Mapping

1. Risk Management & Mitigation (Art. 9): Immutable lineage records support structured risk assessment.
2. High-Quality Training Data (Art. 10): Provenance verification and authenticity checks ensure dataset integrity.
3. Logging & Traceability (Art. 12): Blockchain‑backed immutable event logging across AI lifecycle.
4. Technical Documentation (Art. 11): Automated archiving of system behavior, metadata, and logic.
5. Transparency (Art. 13): Clear documentation of dataset origins, transformations, and ownership.
6. Human Oversight (Art. 14): Context‑rich audit records enabling interpretability.
7. Robustness & Security (Art. 15): Tamper‑evident audit trails ensuring integrity and reliability.