Finance Automation for Sage

An Irish pan-European road freight operator ran finance across five disconnected systems — transport management, telematics, fuel cards, toll feeds, ferry invoices as PDFs — and reconstructed job costs by hand in Excel, weeks after the jobs ran. Sage 50 held the ledger; nobody could say what any given trip actually cost.

We built a platform that computes true per-job profitability automatically: it allocates 101,000+ toll transactions to the exact trip legs they belong to, reconciles ~9,500 fuel-card records a year against vehicle telemetry, reads ferry invoices with AI document extraction, and maps every cost to Sage nominal codes so the ledger and the job-costing view always agree. In its first months it surfaced a €41,000 cost gap nobody knew existed.

Read the full case study, or the guide to job costing automation with Sage.

The reframe that makes this work: cost data is born in operational systems — the fuel card, the toll transponder, the telematics unit — not in documents typed up afterwards. The platform goes to those sources directly, computes the allocation deterministically (the same answer twice, every time, explainable to an auditor), and uses AI only at the unstructured edges, like reading a ferry operator's PDF invoice.

Sage's role doesn't change: it remains the nominal ledger and the system of record. The platform reads Sage through a REST layer over its data, and its computed costs carry the client's own nominal-code mapping — editable by the finance team in a settings screen, not hardcoded — so everything reconciles to the ledger without the automation ever putting the books at risk.

Sage 50 and 200 are kept deliberately simple, which is why they're everywhere in owner-managed and mid-market businesses — and why the work around them sprawls into spreadsheets. The automation layer gives you what the ERP upgrade salesman promises, without the migration:

• Live job or project profitability instead of a month-later Excel reconstruction
• Automatic cost allocation from the systems where costs are born
• Anomaly surfacing — the €41,000 gap was found by the system, not by an accountant with a hunch
• A clean ledger — Sage stays authoritative, and the mapping to nominal codes is explicit and editable

And because the platform is separate from the ledger, it survives a future ERP move: the same architecture maps to Dynamics 365 F&O by swapping the posting adapter from Sage nominal codes to D365 F&O cost categories and WBS elements.

No — freight is just where the proof is (see the freight & logistics industry page). The pattern applies wherever costs are born in operational systems and jobs need true profitability: plant hire and equipment rental, field services, construction subcontracting, distribution. If your team reconstructs job costs in Excel from exports, the shape of the problem is the same regardless of the industry label.

Start with the AI readiness assessment: we'll map which systems hold your cost data, how clean it actually is (never fully — that affects sequencing, not feasibility), and what the first automated allocation should be. Or describe your month-end job-costing routine and we'll tell you what a build would look like against your Sage setup.