Patient Flow Optimisation
Find the hand-off that creates the queue, then model arrival patterns, consultation duration and room use before changing the roster.
38% wait-time reduction in a multi-clinic pilot
Healthcare AI Singapore
Smarter clinics, safer AI under one Singapore-aware roof.
Your clinic runs at 85% capacity yet patients still wait 47 minutes. Your startup's AI tool needs ethics documentation before the next funding round. We fix both.
Lorong AI combines patient flow analytics with practical medical AI ethics guidance. Improve operations today. Show your working tomorrow.
Clinic operations signal
31%appointment utilisation uplift
47mwait-time baseline
Operational intelligence
Analytics that turn waiting rooms into throughput engines.
Good healthcare data analytics gives clinic managers a clear next move. We connect the signals already inside your systems to the decisions staff make every day.
No-Show Prediction
Appointment scheduling optimisation flags likely no-shows early, so teams can offer suitable slots without adding pressure to reception staff.
31% better appointment utilisation
Resource Allocation
Match clinicians, rooms and equipment to demand by hour. The model keeps recommendations visible to the people running the floor.
14% more productive room hours
Treatment Outcome Analytics
Bring outcome measures into one view for service leads. Compare cohorts carefully, document limitations and keep clinical judgement in charge.
1 view for outcome and pathway signals
For healthtech founders
Our AI ethics starter kit gets your team investor-ready faster.
A credible model needs more than a performance score. We organise the evidence around fairness, explainability, validation and responsible data use, with documentation your product and compliance teams can work from.
- Bias audit templateRecord cohort selection, fairness checks and known gaps.
- Explainability reportGive reviewers a plain account of model inputs and limits.
- PDPA and HIMSS alignment checklistMap data handling and controls to the right owners.
- Model validation recordMake testing, monitoring and sign-off easy to trace.
Startup-ready evidence pack
"Lorong AI helped us turn scattered model notes into a clear ethics pack our advisers could review in one sitting."
Jenalyn K.
Healthtech founder, Singapore
Healthtech founder, Singapore
Clinic group case study
How a 12-clinic group reduced patient wait time by 38%.
Lorong AI brought together data from clinic management systems, built a model for appointment slot optimisation and gave clinic managers a live view of queue pressure.
The team tested recommendations with reception leads before wider rollout. Fewer changes landed on staff without context. Better ones stayed.
Discuss a similar pilot38%lower average patient wait time
12clinics using the operating view
31%increase in appointment utilisation after slot recommendations
Practical governance
Navigating MOH, HIMSS and PDPA at once.
Your DPO, clinical leads and product team need the same facts in different forms. We co-develop the evidence so each group can act on it.
AreaWhat we reviewWorking output
Patient data usePurpose, access, retention and consent controls for analytics projects.Data-use register
Clinical model riskValidation method, performance limits, human review and escalation paths.Model risk record
Fairness and explainabilityCohort checks, interpretability needs and communication for affected users.Ethics assessment
Operational readinessMonitoring ownership, incident response and documentation for audits.Control checklist
Start with a focused conversation
Let's design an analytics pilot your clinicians will actually use.
Tell us where the pressure sits. We will shape a practical scope around patient flow analytics, appointment scheduling or medical AI ethics.
Qualified teams can book a 2-hour discovery workshop as the first step.