Transforming animal health through predictive diagnostics, advanced imaging, and personalised treatment plans for companion animals, equine athletes, and livestock herds.
Started with companion and livestock care across the Rift Valley, built on hands-on clinical rigour.
Introduced digital radiography and began archiving structured case data for pattern analysis.
Brought on data scientists to build detection models for subclinical disease and herd-level risk.
Every consultation is supported by predictive models trained on our own case history.
One clinical team, every species we're trusted with — cattle and horses through to dogs, cats and smaller companion animals.
We pair compassionate, hands-on care with machine-learning tools that flag subclinical conditions before symptoms appear — so treatment starts earlier, and outcomes improve.
Fifteen years in small-animal internal medicine; leads model validation for the diagnostic imaging pipeline.
Oversees wearable-sensor deployments across partner farms and outbreak-risk modelling.
Builds the computer-vision and telemetry models behind gait analysis and early-detection alerts.
Each service line runs on the same underlying data platform, tuned to a different patient and a different pace of care.
Digital X-rays, blood panels, and cardiac telemetry are screened by models trained on years of local case data, surfacing findings a first pass might miss — then reviewed by a clinician before anything reaches you.
Wearable sensors track movement, rumination, and temperature across the herd, catching the early signals of disease outbreaks, estrus, and metabolic shifts before they spread or cost you a cycle.
Computer-vision models track stride, load, and symmetry across gaits, identifying subtle asymmetries long before they're visible to the eye — supporting both injury prevention and return-to-work decisions.
A sample of results from cases supported by our diagnostic platform over the past three years.
Short reads on what our case data is telling us, published as patterns emerge.
Tell us what's going on — we'll route this to the right team.