XVN/USD 142.08 ▲2.4% MODELS 128 BLOCK #8,412,907 INFER p95 41ms NODES 34 SYSTEMS NOMINAL
Xvian/Medical AI /

Models that read the body — and show their working.

Benchmarks are easy. Surviving a regulator, a hospital's IT security review and a sceptical radiologist on the same afternoon is the actual problem. That's what this division is built around.

01 / Modalities

Where we operate

MOD_01

Imaging画像診断

CT, MR and plain film. Detection, segmentation and prioritisation for the reporting queue.

MOD_02

Pathology病理

Whole-slide inference at tile level, with region evidence surfaced to the reporting pathologist.

MOD_03

Waveform波形

ECG, EEG and continuous bedside monitoring. Sub-10ms inference on local silicon.

MOD_04

Multimodal統合

Imaging fused with labs, notes and history — the context a single scan can't carry.

[ 1200×900 ]Reading room at night
scan wall lit blue, clinician silhouetted
02 / Clinician first

Built to be overruled

A model that can't be disagreed with doesn't get used twice. Every Xvian prediction arrives with the evidence behind it and a one-click override that is logged, counted and fed back into calibration.

  • Evidence surfacesHeatmaps and region references, generated at inference.
  • Confidence bandsExplicit uncertainty, not a bare score.
  • Override loggingDisagreements are data, and they're anchored too.
  • Case-mix reportingMonthly performance against your population, not the paper's.
03 / Registry

Clinical model registry

updated 22:44 AEST
ModelDomainAUCp95AnchorStatus
thorax-v4.2 Chest CT 0.992 41ms 0x7a1f… CLEARED
retina-v3.8 Fundus 0.981 28ms 0x3c92… CLEARED
histo-v2.1 Pathology 0.964 112ms 0xb14e… REVIEW
cardio-sig-v1.6 ECG stream 0.958 9ms 0x9dd0… CLEARED
onco-fusion-v0.9 Multimodal 0.941 210ms 0x2f77… TRIAL
Regulatory status

CLEARED indicates a clearance held for that model and indication in at least one jurisdiction. REVIEW and TRIAL models are research-use only and must not inform clinical decisions. Jurisdiction detail available under NDA.

04 / Partnership

Bring a question, not a dataset

The best deployments start from a bottleneck in your workflow. Tell us where the queue backs up.

Talk to the clinical team →