Privacy-Aware
Internal privacy diagnostics and direct-identifier checks support controlled synthetic data workflows.
Synthetic Data Infrastructure
Structured synthetic datasets with validation, privacy diagnostics, provenance, and release controls. Real enough to train on, synthetic enough to share. For teams in healthcare, finance, research, anywhere the real data cannot be exposed.
Internal privacy diagnostics and direct-identifier checks support controlled synthetic data workflows.
Validation and quality diagnostics help teams evaluate generated datasets before approved release.
Tenant-aware authorization, provenance tracking and governed release controls form the foundation for enterprise pilots.
Generate structured synthetic datasets through the Aethelis platform and authenticated API workflow.
Built for trusted release
Aethelis keeps privacy, provenance, governance, and monitoring connected throughout the synthetic-data lifecycle.
Protect and control sensitive data throughout the synthetic-data workflow.
See where a data product came from, how it was created, and what happened to it.
Apply governance checks and approval controls before data is released or promoted.
Monitor released data products and surface changes, risks, and issues over time.
Aethelis Technology
Aethelis combines synthetic generation, validation, privacy diagnostics, provenance and release controls in a single workflow. The platform is currently progressing through its v3.1 production hardening stage.
What Aethelis Does
Aethelis helps organizations create artificial datasets for development and research workflows while reducing exposure of original sensitive records. Generated data can move through validation, privacy diagnostics, governance controls and provenance tracking before an approved release.
Built with global deployment in mind, Aethelis is developing infrastructure for organizations exploring governed synthetic data workflows across development, research and enterprise pilot environments.