Case studies
Results across sectors, measured from the baseline.
Each case study shows the situation we found, the systems we designed and what changed after go-live. Metrics are drawn from client operations after deployment.
Retail / Automated vending
Smart vending operations
- Client
- Dedun Vending
- Sector
- Retail / Automated vending
- Team size
- 12 staff across 3 regions
- Stack
- Custom IoT integrationOpenAI GPT-4Google Sheets syncCustom dashboardsRoute optimisation engine
Situation
Dedun Vending operated over 200 machines across multiple locations but relied on manual stock checks and reactive maintenance. Route drivers made unnecessary visits to full machines while empty ones sat idle — costing fuel, labour and lost sales. There was no centralised view of machine health or inventory levels.
Solution
We deployed an AI-driven operations system:
- Real-time inventory monitoring with automated low-stock alerts
- Predictive route optimisation to reduce unnecessary service visits
- Centralised dashboard showing machine health, sales velocity and restock priorities
- Automated reporting for revenue per location and product performance
Results (after 3 months)
30%
reduction in service visits
22%
increase in per-machine revenue
15 hrs
admin time saved per week
Hospitality / Nightlife
Bar and venue hire
- Client
- Good Things
- Sector
- Hospitality / Nightlife
- Team size
- 16 staff, 1 location
- Stack
- Make (Integromat)Anthropic ClaudeAirtableGoogle WorkspaceCustom dashboards
Situation
Good Things managed high-volume venue-hire enquiries, staff rostering and event logistics entirely through manual processes. Enquiries arrived across email, phone and Instagram DMs with no central tracking. Rosters lived in spreadsheets, shift swaps in group chats, and setup checklists in people's heads. Management had no live view of bookings, capacity or labour costs.
Solution
We deployed an internal operations system covering enquiries, rostering and events:
- Centralised enquiry pipeline with automated intake from email and Instagram, status tracking and follow-up reminders
- AI-assisted rostering engine generating weekly schedules from confirmed bookings, availability and labour budget targets
- Digital event runsheets replacing paper checklists, with automated task assignments before each event
- Live operations dashboard: confirmed bookings, venue capacity by date, outstanding enquiries and projected weekly labour costs
Results (after 2 months)
65%
faster enquiry response time
12 hrs
rostering time saved per week
Zero
missed event setup tasks since go-live
Construction / Carpentry
Trade business operations
- Client
- ASK Carpentry and Construction
- Sector
- Construction / Carpentry
- Team size
- 8 staff, residential and commercial projects
- Stack
- Make (Integromat)Anthropic ClaudeAirtableXero integrationGoogle Workspace
Situation
ASK Carpentry and Construction was growing quickly but struggling to keep pace operationally. Enquiries were tracked across text messages and a shared notes app, quoting was done manually with no consistent template, and follow-ups fell through the cracks. Scheduling happened by phone call, staff didn't always know which site to attend, and the director spent hours each week chasing invoices.
Solution
We implemented an end-to-end job and operations management system:
- Centralised job pipeline capturing enquiries from phone, email and website, with automated status tracking from lead to completed job
- Standardised quoting workflow with AI-assisted scope descriptions and automatic follow-up reminders at 3 and 7 days post-quote
- Daily automated schedule summaries sent to each staff member the evening before, from the confirmed job calendar
- Automated invoice generation on job completion with payment-reminder sequences reducing outstanding debtor days
Results (after 3 months)
40%
reduction in outstanding invoices
8 hrs
director admin time saved per week
3×
faster quote turnaround
Infrastructure / Rail services
Infrastructure operations
- Client
- KingRail
- Sector
- Infrastructure / Rail services
- Team size
- 45 staff, multi-site operations
- Stack
- Microsoft 365 integrationOpenAI GPT-4Power BICustom workflow engineSharePoint automation
Situation
KingRail managed complex project timelines across multiple work sites with spreadsheets and manual status updates. Project managers spent hours compiling weekly reports, compliance documentation was scattered, and schedule overruns were common due to poor visibility into resource allocation.
Solution
We deployed project intelligence and compliance automation:
- Centralised project dashboard with real-time status tracking across all sites
- Automated compliance document generation and audit-trail management
- Resource allocation optimisation with AI-driven scheduling recommendations
- Automated weekly stakeholder reporting pulled from live project data
Results (after 4 months)
40%
reduction in reporting overhead
18%
improvement in on-time delivery
30 hrs
admin time saved per week
Your operation has a leak like these. Let's find it.
Every one of these systems started with the same step: mapping where time, revenue and capacity were escaping.