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Healthcare software

Clinical and patient-facing systems that hold sensitive data safely and fit the way a practice already works. Diagnostics support, portals, workflow automation and the integration work underneath all three.

Built in Lahore. We reply same working day.

What makes clinical software hard

Four problems show up on every healthcare build. None of them are solved by picking a framework.

  1. 01

    Patient data has to be provably safe

    Encryption at rest and in transit, access control per role, and an audit trail you can hand to a reviewer. We build those in at schema time, because retrofitting them means rewriting every query.

  2. 02

    Nothing talks to anything by default

    Labs, imaging, the EHR and the billing system each speak their own dialect. We implement HL7 FHIR R4 and write the adapters for the systems that predate it.

  3. 03

    Clinical workflows have many owners

    An order passes through a clinician, a coordinator and a biller before it closes. We map the real path first, including the paper steps, then automate only what is safe to automate.

  4. 04

    Patients use the system too

    Portals and apps for booking, results, reminders and messages. If a patient cannot find their appointment in two taps, the phone rings and the front desk pays for it.

What we build

Four kinds of system. Most engagements start with one and grow into a second.

Diagnostic support models

Machine learning that assists a clinician rather than replacing a judgement: pattern recognition over patient records and imaging, anomaly flags, and a risk score with the inputs shown.

  • Medical image analysis
  • Symptom pattern recognition
  • Risk stratification
  • Clinical decision support

Patient engagement platforms

Patient portals and mobile apps for appointment scheduling, telehealth consultations, medication tracking and secure messaging.

  • Secure patient portals
  • Telehealth integration
  • Medication reminders
  • Health tracking dashboards

Clinical workflow automation

Automation of the administrative load around care: documentation, care coordination, referrals and rosters. The work clinicians did not train for.

  • Automated documentation
  • Care pathway management
  • Referral automation
  • Staff scheduling

Healthcare data analytics

Reporting over clinical and operational data using AWS HealthLake and equivalents, so a question about throughput or outcomes gets an answer from the live system.

  • Population health analytics
  • Operational dashboards
  • Predictive analytics
  • Quality metrics tracking

Security is the first decision, not the last

Compliance shapes the data model, so it goes in before the first migration. We are not auditors and we do not issue certificates. We build the system so the audit has something to read.

  • HIPAA-aware design

    PHI handling, access controls and audit capability designed against HIPAA requirements from the first schema.

  • SOC 2 ready architecture

    Security controls and monitoring built so a SOC 2 audit has evidence to read rather than gaps to note.

  • Data encryption

    Encryption at rest and in transit, using protocols your auditor already knows.

  • Audit logging

    Every data access and system action recorded, queryable, and retained.

The stack underneath

Technology used on healthcare builds, by layer
LayerWhat we use
CloudAWS HealthLake, Google Cloud Healthcare API, Azure Health Data Services
AI and MLLangChain for clinical NLP, custom models, medical image processing
InteroperabilityHL7 FHIR R4, SMART on FHIR, CDA and C-CDA
SecurityEnd-to-end encryption, OAuth 2.0, role-based access control

Tell us which part of the clinical day is manual.

A 30 minute call. We walk the workflow with you, say what can be automated safely and what should stay in human hands, and tell you if this is not our work.

Book a call
First reply
same working day
Built in
Lahore, Pakistan
WhatsApp, any time+92 335-0706014