Where the money is

The business case splits the potential across three levers, all calculated from the customer’s own files.

• Fewer admin hours. Collection, cost allocation, controls and reporting are automated. AI reads the leasing contract when a vehicle is created; a person approves every field. Data handling alone was estimated at 700–800,000 DKK a year.
• Lower consumption, fewer deviations. Four controls run on raw data: duplicate invoices, petrol and diesel on the same card the same day, impossible mileage jumps, missing readings. A flag becomes a ready-written dispute in one click. 5–10% of a ~20M DKK vehicle spend is millions.
• Better fleet decisions. Lease expiries, payments and consumption sit together across all six leasing companies, so capacity and replacement can be judged before more vehicles are ordered. Many companies do not need more vehicles. They need better data on the ones they have.

How it works

• Collect data. The finance extract and supplier files are read in. Seven supplier formats are recognised automatically, from fuel cards to charging tags.
• Build the overview. One record per number plate: leasing, driver, consumption, service, damage and history. Every number reads from the same database.
• Prioritise actions. Deviations and deadlines become a list with an owner, not just a chart. Service is flagged 30 days ahead, lease expiry 90 days ahead.
• Automate the workflows. AI drafts reminders, service bookings and disputes. Nothing is sent before a person approves it.
• Measure the effect. Management reports with KPIs calculated by the system, not by a language model, compared against your baseline.

What it does day to day

• QR sticker in every vehicle. The driver scans it and reports an accident, damage, a fault or the odometer from their phone. No login, no app.
• The whole fleet in one live view. Vehicle count, EV share, annual run-rate, lease expiries, service and deviations, all from the same database.
• Ask the fleet. “Who drives CK 24 118?” “How many EVs do we have?” Ask in Danish or English and get answers from your own data. The model says so when the answer is not in the data.
• Optimisation report. It reviews vehicles, leases, invoices and consumption and delivers recommendations with an estimated saving in DKK, prioritised by money, not by technology.
• Alerts per vehicle. Winter tyres on 1 September, service 30 days ahead, lease expiry 90 days ahead. You set the rules, the system watches.
• Cost per vehicle. Fuel, charging, oil, service, parking and bridge tolls are all allocated to the number plate, with VAT handled by plate type and export ready for the finance system.
• Your own feature. About 60% is finished software; the last 40% is shaped to your chart of accounts, systems and workflows. New requests are included in the fixed price and built into your system.

The case so far

• 219 vehicles imported from the customer’s own extract, with a report for every rejected row.
• 15,600 postings from real supplier files verified against the system’s cost allocation.
• 87–99% automatic plate matching across the seven supplier formats.
• 1–2M DKK in identified annual savings potential. A conservative range, not yet a measured saving. The realised effect is tracked against baseline.

Who it is for

Facility management and service companies, trades and installation, logistics and distribution, utilities and maintenance, and public or private operations with 100+ service vehicles or spread-out teams. Less relevant for small fleets without real admin overhead, or for anyone who just wants another dashboard without changing how they work.