ReactiveProactive
Anticipate risks before they escalate, with early-warning models that learn each person’s baseline.
Health AI · Made in Australia
Healthcare that sees what’s coming.
Pi MedTech builds AI that turns everyday health data and biological images into early, personalised insight, so patients, clinicians and researchers can act before problems escalate.
- Peer-reviewed in Communications Biology
- Founders publish in JACC, IEEE & Neuro-Oncology
Our approach
Healthcare is still mostly reactive.
We’re building the alternative.
Most care starts after something has already gone wrong. The signals were often there earlier, spread across wearables, records, images and daily life. Our AI brings them together and turns them into decisions people can act on.
EpisodicContinuous
Real-time insight between appointments, from the devices and data people already have.
GenericPersonal
Guidance tailored to the individual, so clinicians can personalise care and patients can make informed choices.
Our mission is simple: to help every person reach their full health potential.
Solutions
Three products, one foundation.
Each product applies the same core: clinically grounded AI, privacy by design, and insight a person can act on.
CardioPlus
Safer recovery at home for heart patients after hospital discharge.
CardioPlus monitors vital signs through connected wearables, flags early signs of complications, and keeps patients, families and care teams connected, with the aim of preventing avoidable readmissions.
- Continuous monitoring of heart rate, blood pressure and oxygen saturation, plus symptom logging
- Early-warning AI alerts that detect changes from each patient’s baseline
- Medication support with reminders, adherence tracking and interaction checks
- Connected care through telehealth, secure messaging, a caregiver portal and an SOS button
LifeSync
Diabetes management that looks beyond the glucose number.
LifeSync combines activity, connected devices, nutrition and emotional wellbeing into a single picture, then uses machine learning to surface the patterns that matter for each person.
- Holistic data from glucose monitors, wearables, meals and mood
- Personalised insights to improve Time in Range and reduce glucose variability
- Clear daily and weekly trends so users can adjust early
PiNet: from biological images to network insight.
PiNet extracts complex biological structures from microscopy, CT, X-ray and other imaging, and reconstructs them as mathematical graphs. Researchers can then measure connectivity, topology and dynamics, and find patterns the eye can’t see.
- Works across imaging modalities, from cell cultures to whole-organ scans
- Turns images into nodes and edges for quantitative network analysis
- Tracks how structures change over time
Validated in peer-reviewed research published in Communications Biology (Nature Portfolio), 2021.
Live extractionPiNet
Links
Junctions
Microscopy time-lapse
“AI isn’t a feature. It’s our foundation.”
We use AI to reimagine what’s possible in healthcare, not to replace people. Our tools give patients, clinicians and scientists better information, sooner.
Founders
Built by scientists who ship.
Deep expertise in cancer biology and machine learning, with years of turning research into tools that work in the real world.
Ana is a cancer biologist focused on turning laboratory discoveries into new therapeutic strategies. Her PhD in Cancer Biology from the University of Adelaide uncovered new insights into the tumour microenvironment, immune interactions and cancer progression, using advanced CRISPR and in vivo models.
As a Research Associate at the Centre for Cancer Biology, she develops and tests novel therapies for glioblastoma, one of the most aggressive brain cancers, using patient-derived organoids. At Pi MedTech she leads the scientific vision and the company’s mission to improve patient outcomes.
- PhD, Cancer Biology
- Neuro-Oncology
- Cell Reports Methods
- Translational research
Mohsen is a computer scientist working where machine learning, health and signal processing meet. He is a Lecturer at the University of Adelaide and a Research Fellow at the Australian Institute for Machine Learning (AIML), where he translates AI into practical healthcare solutions.
His PhD in Computer Science received the Dean’s Commendation for Doctoral Thesis Excellence. He is an Associate Editor of IEEE Access, is active in the IEEE Engineering in Medicine and Biology Society, and serves on a university Human Research Ethics Committee.
- PhD, Computer Science
- JACC
- IEEE
- Royal Society Open Science
- Nature Portfolio
Request a demo
Let’s talk about what’s next.
Whether you’re a clinician, researcher, health organisation or investor, we’d like to hear from you. Tell us a little about your interest and we’ll get back to you within two business days.
- hello@pimedtech.com
- Australia · working with partners worldwide