Clinica - Multi-Department Clinic Operations Console with AI Assistant
AI-Native Clinic Operations Platform
Built a multi-department clinic operations console with appointment management, department load tracking, staff performance, resource utilisation and an AI assistant for staff queries - shipped from clickable AI prototype to production in 14 weeks.
Most of our work is under NDA. Per agreement, we can share the work but not the company details - all names and identifying information shown here have been changed.
Impact
2 weeks scope, 3 weeks clickable AI prototype, 9 weeks production build with EHR integration.
General, Cardiology, Paediatrics, Orthopaedics and Obs/Gynae rendered in one workspace.
Built-in AI assistant lets staff query the operations database in natural language.
Built to PDPA + MOH-IM8 with HIPAA-aligned audit trail and role-based access.
The Problem
Clinica's clinic network was running daily operations through fragmented systems - appointments in one tool, staff scheduling in another, bed occupancy on a wall whiteboard - with no consolidated view for clinic directors or department leads.
Our Solution
We delivered a single operations console with live appointment volume, department load, staff performance, resource utilisation, and an AI assistant for natural-language queries - validated through a clickable AI prototype before any EHR integration.
The Challenge: Operations Across Departments
Clinic operations live across appointments, staff, beds, equipment and medication - usually in five different systems. Clinica's directors needed one place to run the day from.
Fragmented Operations Data
Appointments, staff schedules, bed occupancy and equipment usage lived in separate systems with no shared identity layer. Directors reconciled state by hand each morning.
No Real-Time Department Load
Department leads could not see live load, completion rate, or no-show signals during the day - only end-of-day reports. By then it was too late to rebalance.
AI Without Clinical Context
Generic chatbots don't understand clinic-specific operations. Staff needed an assistant that knew the schedule, the room, the doctor, and the patient flow.
PDPA + MOH-IM8 Compliance
Singapore's MOH-IM8 imposes strict data-handling, audit-trail and access-control requirements on healthcare systems. Every flow had to be PDPA-compliant by default.
Our Approach: 3 Phases in 14 Weeks
Discovery & Scope
Weeks 1–2: embedded with Clinica's clinic directors, department leads and operations teams. Mapped every flow - appointment scheduling, staff assignment, resource utilisation, AI assistant queries - across the five clinical departments.
AI-Driven Clickable Prototype
Weeks 3–5: built a fully interactive prototype with mocked appointments, department load, staff performance and AI assistant responses, so the team could click through every flow before any EHR integration.
Production Build & Launch
Weeks 6–14: shipped the production console with live appointment volume, department load, staff performance, resource utilisation, an AI assistant trained on operations context, and full PDPA + MOH-IM8 audit trail.
Why It Works: Outcome-Based Differentiation
Speed to Value
Most clinic operations platforms take 9–18 months to ship. We delivered a clickable AI prototype in 5 weeks and a production console in 14, with full EHR integration.
AI-First Prototyping
Every flow - appointments, staff performance, resource utilisation, AI assistant - was validated in the prototype before any production code touched real patient data.
Single Accountable Team
Design, AI prototyping, EHR integration, and front-end engineering under one roof - no handoff between an app studio and a healthcare-IT vendor.
Outcome-Based Engagement
Clinica paid for milestones and live operations functionality, not hours. Our incentives were tied directly to shipping a console that directors opened every morning.
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