Finance and accounting automation, built for a function that can't afford to guess

Where finance automation actually pays off

The finance work worth automating is the work that is both high-volume and rule-shaped: reading an invoice and matching it to a purchase order, categorising a transaction, sending a dunning reminder on a schedule, pulling the same numbers into the same report every month. These are tasks your team does hundreds of times, the same way each time, and every one is a chance for a typo, a missed deadline, or a number that lands in the wrong account. Software does them the same way at 3am as at 3pm.

We do not automate judgement. Deciding whether to extend credit, how to treat an ambiguous transaction, or whether a control is adequate stays with your people, because that is where their expertise earns its keep. What we take off their plate is the mechanical layer underneath: the reading, matching, typing, and moving that fills a finance team's day and adds no insight. When that clears, your team spends its time on the work that actually needs a human.

• Accounts payable: read invoices, match to POs and receipts, prepare postings
• Accounts receivable: raise invoices, send reminders, flag overdue accounts
• Expenses: capture receipts, categorise, route for approval
• Bank reconciliation: match transactions to the ledger, surface the exceptions
• Reporting and close: assemble management reports and month-end packs

Validation first, because a wrong number is worse than a slow one

In marketing, a bad automation sends an awkward email. In finance, a bad automation pays the wrong supplier or misstates a report. That difference shapes how we build. Every automation that reads or writes financial data has validation in front of it: does this invoice total match its line items, does this transaction reconcile, does this figure sit inside a sane range for this account and period. When something fails a check, the workflow stops and flags it for a person rather than pushing a bad number downstream.

We would rather an automation refuse to act than act wrongly. A flow that quietly catches ten exceptions a month and hands them to a human is doing its job, not failing at it. The goal is not to remove people from finance, it is to remove the mechanical typing so people can spend their attention on the ten things that genuinely need a decision, with clean data in front of them when they make it.

Human-in-the-loop on anything that moves money

We never let an automation send a payment on its own. Reading an invoice, matching it to a PO, checking the maths, and preparing the posting: all of that we automate. The release of funds stays behind a human approval, in your accounting system or banking portal, with the automation presenting a clean, validated summary for the person to approve or reject. The machine does the preparation; a person makes the call.

The same principle scales down. Auto-categorised transactions can be posted directly when the confidence is high and the amounts are routine, while anything unusual is held for review. You set where those lines sit, and we make them explicit rather than hidden. You always know what runs automatically, what waits for a human, and why, and you can move those thresholds as your trust in a given flow grows.

An audit trail you can actually defend

Finance lives and dies by traceability, so everything our automations do is logged: what was read, what decision was made, what was written, and when. When your auditor or your CFO asks why a transaction was coded a certain way, the answer is in the log, not in someone's memory. This is not an add-on we bolt on at the end; it is how the workflows are built, because an automation you cannot explain has no place near a ledger.

That traceability is also what makes the automation safe to trust over time. Every posting links back to its source document and the rule or model output that produced it. If a categorisation looks wrong three weeks later, you can trace exactly how it happened and correct the rule, rather than guessing. Good automation makes your books more auditable than manual work, not less.

• Every read, decision, and write is timestamped and stored
• Postings link back to source documents and the rule or model output behind them
• Failed validations are logged as exceptions, not swallowed silently
• Alerting when a flow breaks, a login expires, or a source changes

Built on your tools, owned by you

We connect to the accounting and ERP systems you already run through their APIs, whether that is a modern cloud ledger or an older on-premise system, and we do not ask you to rip anything out. The automation layer sits alongside your stack, reading and writing through the same interfaces your team uses, so nothing about your system of record changes except that it stays cleaner and more current.

When we hand over, you own all of it: the workflows, the code, the documentation, the credentials, running on your own infrastructure and accounts. We favour self-hosted n8n so your financial data stays under your control, which matters a great deal in Europe under GDPR. If you ever want to bring the work in-house or move to another partner, everything comes with you. We are a studio that ships you an asset, not a black box you can never turn off. And we are not licensed accountants or tax advisers: we build the plumbing, your finance professionals own the judgement and the regulated advice.