From complex data to clear action.
Seven stages, each recording provenance, turning raw multi-omics into decisions clinicians and researchers can act on.
High-quality data across all six omics layers, with pipeline provenance recorded on ingest.
Harmonise diverse datasets into one biological frame, with quality control gates that block rather than annotate.
Machine learning surfaces patterns and signatures across layers that single-layer analysis cannot resolve.
Map findings to pathways, networks and mechanism — and classify through a transparent criteria engine.
Risk, progression and treatment response, with calibrated uncertainty attached to every estimate.
Clear, interpretable, clinically relevant output as HL7 FHIR Genomics resources.
Better decisions and improved outcomes — measured, not assumed.
AI at the core. Biology at the centre.
Genomics, transcriptomics, proteomics, metabolomics, microbiome and epigenomics enter the platform.
Secure ingestion, harmonisation and quality control unify diverse data into a single biological frame.
Machine learning, systems biology, knowledge graphs and causal inference decode complexity.
Risk and outcome prediction, therapeutic insight and research acceleration built on the engine output.
Interactive dashboards, clinical and research reports, developer APIs and partner integrations.
An interpretation you can regenerate in four years.
Every result records the evidence snapshot, rule set version, model version, input observation versions and container digests that produced it. Reproduction is a query against the provenance record, not an archaeology exercise.
Run it on your data.
Anchor partners commit a defined case volume and named reviewers — and get a real say in the roadmap.