Anonymised under NDA. Pulled from our full library and ranked by how closely each matches what you and Hendrik are running. Tom’s story above is the named one. Below: the five other audits that map directly to Van Leeuwen.
#1 · A multi-team services business (NDIS)
~2,200 hrs/yrrecoverable · $120K waste
What the audit found: the owner personally built the next day’s schedule every single day, 7 days a week — “it takes me between three and five hours a day to get it done” — that’s 28 hrs/wk just rostering. Another 30 minutes a day went to reformatting and sending text messages individually to ~50 staff from a phone. Staff often didn’t know if they were working until late the night before. Lead response time sat at 1.5 days — losing about one lead a month at near-100% conversion. On top of that, $6,000/yr was being paid for an abandoned subscription that nobody was using.
AI opportunities mapped
Rules-based AI scheduling engine with voice input (returns 21 hrs/wk to the owner); CRM lead pipeline closing the 1.5-day response gap; central contact database replacing scattered Trello / email / Messenger searches; AI-generated progress reports.
How it maps to Van Leeuwen Green: this is the closest mirror in our entire library to your scheduling reality — one person (you) rostering teams every day, manually. Same fix would apply: AI drafts tomorrow’s 13-team schedule based on jobs, locations, skills and team availability, and you approve in minutes instead of building from scratch. Bonus from this audit: the recommended new stack actually cost the business less than what they were already paying, once the abandoned subscriptions were cancelled.
#2 · A B2B field-team distributor
~7,100 hrs/yrrecoverable · $104K waste
What the audit found: four field reps with zero CRM activity logging — “they do not want to do it” — so no visibility on calls, visits or outcomes. The reps were burning 128 hours a week between them on comfort visits to low-value $5–7K/yr accounts instead of winning new ones. Of 150 NZ leads, 40 were worthwhile but reps called once, left a voicemail, then stopped. The owner ended up spending an entire weekend manually qualifying all 150 leads himself. A 4-system cross-reference (Outlook, GPS, accounting, HubSpot) was confirmed “not working”. The account base had been net-flat for 2 years — gaining ~40 accounts/yr but losing roughly the same.
AI opportunities mapped
AI auto-qualification of inbound leads; a rep activity dashboard with alerts when teams aren’t producing; 60-day no-activity churn alert; consolidation of the 4 disconnected systems; AI-built sales playbook from call patterns.
How it maps to Van Leeuwen Green: you have 13 teams in the field and no real-time visibility on what they’re doing day-to-day. You’re also acting as the manual qualifier for every inquiry that hits your phone. The fix is twofold: an AI activity layer over your teams (per the distributor) and an AI qualifier that takes the inbound triage off your plate.
#3 · A high-volume customer-onboarding business
~3,500 hrs/yrrecoverable · $253K waste
What the audit found: 300–400 new customers a year onboarded on a fully manual stack — dragging people through pipelines by hand and re-entering the same data across 5 tools. 15 hrs/wk across two people went to spreadsheet management alone. Revenue was leaking because only ~1 in 3 customers ever got properly invoiced. A single automation recovered $47,923/yr of missed revenue and was built in half a week. They also had no email marketing — ~50% of converters had inquired in earlier months with no nurture at all. Six years of decisions had been made on gut feel with no dashboard.
AI opportunities mapped
Automated instalment tracking & invoicing (the $47K recovery); role-fill acceleration pipeline; onboarding automation returning 22 hrs/wk; BI dashboard replacing gut-feel decisions; automated nurture for past inquiries.
How it maps to Van Leeuwen Green: this is the Emma role at high volume. Manual follow-up, manual data entry from the ServiceMate intake form into job records, manual lead nurture. Most of that work becomes AI doing the work and Emma reviewing — the same pattern you flagged yourself on the call (“we’re paying for someone to just do a lot that maybe we could automate”).
#4 · A multi-office real estate group
15,200 hrs/yrrecoverable · $958K waste
What the audit found: 2,987 appraisal contacts sitting in the CRM with zero follow-up comments, and a separate pool of 1,100 unfollowed sales opportunities. The owner’s own process map identified 19 hrs of AI-replaceable work per sale — across 800 sales/yr that’s 15,200 hours. No call tracking on the sales side (agents used personal mobiles). No referral outcome tracking. 200+ Zapier automations held together with no central marketing task board. Pre-listing emails sent ad hoc — “I don’t know whether it goes out every single time or not”.
AI opportunities mapped
API integration to run the 19 hrs/sale of automatable work; automated referral tracking (speed-to-lead, outcomes, conversion per agent); auto task assignment per marketing package; one-click content generation from templates + property data; central marketing task board replacing inbox-based allocation.
How it maps to Van Leeuwen Green: this is the database reactivation gap you described and the speed-to-lead opportunity. Old customers and stalled leads sit untouched in ServiceMate — AI re-engages them automatically with seasonal offers. When a new inquiry lands, an automated SMS goes out within 60 seconds to capture the missing details (photos, surname, property), instead of you chasing them later. Speed-to-lead inside 5 minutes lifts conversion by roughly 200%.
#5 · A founder-led marketing agency
~1,160 hrs/yrrecoverable · $93K waste
What the audit found: classic founder bottleneck — the agency was capped at 1–2 new clients at a time because each one needed 6–8 weeks of intensive discovery that only the founder could do. Process mapping took 2 full days of write-up per client, relying on memory and notes. A 60-page market intelligence report went underused: “it’ll take me three or four days to really read that document”. Reporting was fully manual. Quality assurance broke down whenever the founders got busy. Two team members duplicated work 3 of 5 days. A founder personally answered Facebook Messenger for every client.
AI opportunities mapped
AI-assisted discovery built from call transcripts (returns $35K/yr); auto-generated campaign messaging from the market report; client-facing portal; automated monthly reporting consolidation — enabling the business to scale from 7 to 14 staff without adding founder hours.
How it maps to Van Leeuwen Green: same shape as your situation with Hendrik. He’s the brain on quoting, you’re the brain on scheduling and ops — every transaction needs your hands on it. AI lifts the operational layer so the founder-bottleneck stops being the cap on growth. You and Hendrik focus on judgement calls; AI handles the production work underneath.