The Genomics Intelligence Platform runs as three connected layers — intelligence, digital biology and care execution — unified by a lifelong Digital Twin and built on open standards.
Each layer is a product in its own right — and each makes the layer above it possible, from raw biology to care that reaches the patient.
The biological intelligence engine — fuses six omics layers with AI and systems biology into actionable insight.
Virtual cells and the personal health cloud — simulate biology, and model the individual over a lifetime.
Turns intelligence into coordinated, proactive care — across the system and at the point of care.
Stateless interpretation scales horizontally; a shared, stateful evidence substrate keeps every result consistent and reproducible years later.
Sequencing output and clinical data enter through the API gateway — FASTQ, BAM/CRAM, VCF, FHIR.
Annotation, prioritisation and reasoning over a federated evidence graph, with human review.
Structured, interoperable results in HL7 FHIR Genomics, dropping into existing EHR/LIMS workflows.
Every result accretes into a longitudinal, computable model of the patient — reinterpretable over time.
Substrate: event streaming · data lakehouse · vector DB · knowledge graph · Kubernetes on regional / sovereign cloud.
Every assertion links to the criteria and citations behind it — auditable years later.
AI augments the expert; a named clinical reviewer stands behind every result.
FHIR and GA4GH built in, not adapted — interoperability is the strategy.
Cloud-agnostic Kubernetes keeps data inside the borders that require it.
Anchor sites are partners, not customers — early capability and a real say in the roadmap.