Case study · Healthcare

Patient-facing healthcare application

Routine enquiries moved out of the call queue entirely, and the clinical team now sees a triaged inbox rather than an undifferentiated one.

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Challenge

A care provider's patients were booking, rescheduling and asking routine questions by phone. The call queue was the bottleneck for everything, and clinical staff were absorbing administrative load that had nothing to do with care.

Approach

We designed and built the patient application covering appointments, records access, secure messaging and pre-visit questionnaires, with an NLP triage layer that routes incoming messages to the right team and answers the routine ones from approved content, escalating anything clinical to a human.

Outcome
Routine enquiries moved out of the call queue entirely, and the clinical team now sees a triaged inbox rather than an undifferentiated one.

More work

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Approach: We consolidated the record onto a single scheduling, records and referral platform, and built a record-linkage model to resolve the duplicates that had accumulated over years of parallel data entry. Clinician-facing screens were designed with the staff who use them between appointments, not around them.

4 sites

delivered

consolidated onto one patient record

Python
PostgreSQL
Azure
Docker
Kubernetes
HL7 FHIR

Outcome

One patient record across all four sites, with referrals moving between them without re-keying and a clean audit trail behind every merge the model proposed.

Sector: Healthcare

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Approach: We built the storefront and order platform, then wired a demand model into the merchandising layer. Sales, stock position and campaign calendar feed a forecast that ranks what to surface and flags lines heading for a stockout before the promotion goes live.

32%

reduction

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Next.js
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Databricks
PostgreSQL
AWS
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Outcome

Merchandising decisions moved from a weekly meeting to a daily ranked list, and the stockouts that used to end campaigns early became a pre-campaign warning instead of a post-mortem.

Sector: FMCG

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