JurnX Labs — Experiments in Digital Trust

Jurnx Labs is where I experiment with ideas around trust, provenance, and verifiable data.

It’s a space to test, build, and share lightweight technologies that make data integrity accessible to everyone — from developers to enterprises to AI systems.

• Developer tools for verifiable event recording

• APIs for auditability and shared trust

• Privacy-preserving verification between systems

• Exploring non-blockchain trust models (e.g. DAG, hybrid, or local proofs)

Many of the design decisions explored in Jurnx Labs are evaluated against a personal medical record (PMR) use-case.

This is not a product or personal narrative. It is used as a reference model because medical records impose strict, non-negotiable constraints on systems design: accuracy, auditability, provenance, privacy, and long-term integrity.

If a system cannot reliably support a longitudinal personal medical record — where historical data must not silently change, summaries must be traceable, and every transformation must be explainable — it is unlikely to support high-trust use-cases elsewhere.

PMR serves as a stress test for the Jurnx trust layer: forcing correctness, reversibility, and verifiable history by design.

This work is evaluated against a personal medical record reference use-case, where auditability and longitudinal integrity are mandatory.