003 / Case Studies

AI in the loop, from brief to production.

Selected work delivered by Genact's founding team — and how AI agents were used at every stage: planning, execution, and delivery.

CASE 01 — Workforce Platform · QSR
IN PRODUCTION SINCE 2024
Nationwide restaurant workforce — the super-app's operating environment

Employee super-app for a nationwide restaurant chain

A full digital ecosystem for a nationwide restaurant workforce: an iOS/Android app, a web admin dashboard, and a tablet QR time-attendance system — six integrated codebases serving thousands of crew members daily.

QR + biometric clock-in/out E-schedules Points & rewards redemption Certifications News · surveys · manuals Push notifications Facial-recognition device sync BigQuery analytics EN / BM
300+
API endpoints
175+
Admin screens
100+
Data models
22
Scheduled jobs
How AI shipped it
Planning

AI-drafted migration roadmaps and risk assessments for major upgrades — Laravel 8→13, PHP 7.4→8.3, Vue 2→3 — each broken into staged phases so QA failures could be triaged cleanly.

Execution

Multi-agent refactoring migrated 115 admin forms in parallel. AI security audits drove OWASP hardening: timing-safe JWT verification, server-side token minting, XSS sanitisation, and CVE-led dependency replacement.

Delivery

AI-generated audit and architecture docs keep the system maintainable; incremental staging-to-production releases shipped the entire framework modernisation with zero downtime.

CASE 02 — Kitchen Intelligence · QSR
IN DEVELOPMENT · POC JULY 2026
Real-time kitchen scheduling dashboard — Production Monitor

Production Monitor — when to cook, computed in real time

An offline-first PWA that tells kitchen crew exactly when to start each cooking batch — a walk-back scheduler works backwards from hourly sales forecasts through equipment capacity and cycle times, so batches finish exactly when demand arrives. Built to cut stockouts and waste across a nationwide restaurant fleet.

16-product live cook dashboard Walk-back batch scheduler Behind-schedule alerts Equipment-busy guards Waste logging & audit Crew / Store / HQ roles Offline-first sync engine EN / BM
70
Screens designed
46
Automated tests
60s
Sync cadence
7
Delivery phases
How AI shipped it
Planning

AI co-authored the full business requirements document, build spec, data-flow diagrams, and a 70-screen UI inventory — and helped re-plan a single-store kiosk concept into a fleet-wide PWA architecture in a single day.

Execution

Spec-driven build across seven phases: the batch-scheduling algorithm, the idempotent offline sync engine, and role-gated UI were implemented with AI agents and locked in with 46 unit tests on the core business logic.

Delivery

From approved spec to a working build in days, not months — now in active development toward a proof-of-concept rollout, fully documented with implementation-status reports and architecture diagrams generated alongside the code.

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