The COPD digital twin

See COPD deterioration before the readmission.

Muggle Chi gives every COPD patient a predictive digital twin after discharge. It learns each patient's normal and alerts the care team while there is still time to act at home. Patients recover where they feel safest, and hospitals avoid the readmission.

Live productClinician in the loopBuilt in Riyadh

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Synthetic demo data

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Designed for Saudi healthcare
  • SFDA SaMD pathway
  • Hosted in the Kingdom
  • PDPL data handling
  • FHIR R4 · NPHIES-ready

The problem

COPD patients go home into a blind spot.

Between discharge and the next appointment, nobody sees the slow slide. The health system usually finds out in the emergency department.

23%of COPD patients are readmitted within 30 days of discharge

Deterioration is silent

SpO₂, breathing rate and heart rate drift for days before the patient feels unwell.

SAR 16–20kcost of each avoidable readmission to a Saudi hospital

Wearable data is not clinical data

Consumer devices measure the same thing in very different ways. Clinicians cannot act on numbers they cannot trust.

~8 weeksto evaluate, source and deliver a monitoring device today

Devices arrive too late

By the time equipment reaches the patient, many are already back in hospital.

Post-discharge coverage

30 dayscontinuous monitoring window after every discharge

The philosophy

Precision foresight in modern healthcare.

Modern medicine shouldn't wait for symptoms to escalate. Muggle Chi turns continuous physiological data into proactive clinical decision support, a bridge between recovery at home and peace of mind for the hospital.

  • Anticipate risk trajectories before acute events occur
  • Fits into existing clinical workflows
  • Focused entirely on measurable patient outcomes
Speak with our clinical team →

The platform

Three engines. One trusted view of every patient.

A living digital twin for each COPD patient, built on signals clinicians can rely on.

Engine 1

Clinical-grade data layer

We assess wearables for clinical validity and turn their signals into one trusted stream a clinician can act on.

Any device in · Medical-grade signal out
Engine 2

Predictive digital twin

Each twin learns the patient's personal baseline and raises an explainable risk score when they start to drift.

Baseline learned · Drift flagged
Engine 3

Validated device marketplace

We match each patient to a validated device through certified distributors, so monitoring starts in days, not weeks.

Right device · Days, not weeks

What the twin watches

A living picture of each patient, built from three sources.

Signals from a validated wearable, a quick daily check-in and the patient's medical record come together in one twin. It learns what normal looks like for that person, so small changes stand out early.

WearableDaily check-inMedical record
Blood oxygen (SpO₂)Wearable
Breathing rateWearable
Heart rateWearable
Breathlessness and coughDaily check-in
Rescue inhaler useDaily check-in
Diagnosis and historyMedical record

The care team view

One screen. Every patient. Ranked by risk.

Clinicians see each patient's vitals against their own baseline, the direction their risk is moving, and a clear recommendation. The system flags, the care team decides.

  • Personal baselinesEach alert compares the patient with their own normal, not a population average.
  • Explainable scoresEvery risk score shows what drove it, so clinicians can trust and act on it.
Patient P-1001Streaming
SpO₂89.2%baseline 91.5
Resp. rate26baseline 18
Heart rate105baseline 78
Care team alert Drifting from baseline Recommend a call today
Risk index
52of 100
High

Synthetic demo data

How it works

From discharge to early action, in four steps.

1

Enrol

A discharge risk screen identifies the patients who need monitoring most.

2

Match and stream

The patient receives a validated wearable, and vitals stream into their twin.

3

Score

The twin compares each reading with the patient's own baseline and updates their risk throughout the day.

4

Act

The care team gets a prioritised alert to call the patient or adjust treatment.

Clinician in the loop: the system flags, the care team decides.

A day with the twin

The phone call that keeps a patient at home.

An illustrative day for a patient recovering after a COPD admission.

  1. Morning check-inTwo quick questions on breathing and cough. Readings sync from the wearable.
  2. A quiet driftBlood oxygen and breathing rate start moving away from this patient's own baseline. They still feel fine.
  3. Care team alertedThe patient rises to the top of the nurse's list, with the reasons shown.
  4. A call, not an ambulanceThe nurse calls, reviews the inhaler routine and books a next-day clinic visit.
  5. Recovering at homeTreatment is adjusted in clinic. No emergency visit, no readmission.

For hospitals and health clusters

Under AR-DRG, the cheapest readmission is the one that never happens.

With bundled payments and NPHIES validation, a 30-day COPD readmission is a cost the hospital carries. Muggle Chi helps turn that risk into better outcomes and a stronger margin.

  • Protect DRG marginsCatch deterioration early and avoid unpaid readmission stays.
  • Shift care to outpatientSee flagged patients in clinic instead of the emergency department.
  • Offer a new recovery serviceGive patients a premium post-discharge monitoring programme.
  • Pay for resultsCommercial terms are aligned to verified outcomes at each site.

Evidence and regulation

Evidence first, then SFDA clearance.

We are building the clinical case step by step, with regulation and data protection designed in from day one.

Phase 1

Retrospective validation

Testing the risk index against historical Saudi patient data.

Planned
Phase 2

Prospective pilot in Riyadh

A controlled hospital pilot measuring how early we warn and how many readmissions we prevent.

In preparation
Phase 3

SFDA submission

Software as a Medical Device authorisation, supported by the pilot readout.

Planned
ISO 13485Quality management
IEC 62304Software lifecycle
ISO 14971Risk management
NCA controlsCybersecurity

These are the standards we are building to. Certification status is shared with partners on request.

Our vision in motion

Recovery at home, watched over.

About Muggle Chi

We don't just collect health data. We make it predictive, clinical and actionable.
Built by engineers, governed by physiciansAn experienced AI, cloud and data team works alongside a clinical advisory board of practising physicians.
Starting with COPD in Saudi ArabiaAligned with Vision 2030's shift of chronic care from hospital to home. Heart failure and diabetes come next.
Headquartered in RiyadhWorking with health clusters and private hospitals across the Kingdom.

The team

Three disciplines. One mission.

Clinical expertise, technical precision and strategic leadership, working toward one goal: better outcomes for patients after they leave hospital.

I

Clinical advisory board

Practising clinicians and specialists who keep every insight grounded in real patient care. Their judgement shapes when and how the care team is asked to act.

II

Technology team

Engineers and data scientists who turn complex physiological signals into clear, actionable intelligence, built for accuracy, speed and clinical reliability.

III

Strategic business team

Healthcare operators focused on lasting partnerships and alignment with health institutions, so Muggle Chi delivers measurable value at every level.

Get in touch

See the digital twin in action.

We run guided demos for hospital leaders, clinicians and partners. Tell us a little about you and we will be in touch.

Hospitals and clustersCliniciansInvestorsDevice partners

Email mugglechioffice@gmail.com
Riyadh, Saudi Arabia

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