
The bottleneck was never typing
Every nearshoring provider is talking about AI. Here is what we actually point it at — requirements, test coverage and code review — and why that is a deliberate choice rather than a modest one.


Matching open invoices against incoming payments is still surprisingly manual in most finance departments. We are building a solution that reconciles SAP invoices with bank statements largely automatically — reducing manual effort while raising process quality.

Reconciliation is time-intensive, error-prone, and heavily dependent on individual employees’ experience. The goal: automate the matching of SAP invoices and bank movements without losing professional control, while increasing transparency and auditability.

Reduced manual effort, faster reconciliation cycles, and improved transparency across receivables and payments.

An SAP-adjacent integration and automation layer that intelligently merges invoice data and bank information from different sources, producing reliable matching proposals or automatic assignments — with faster recognition of matches and fewer manual verification steps.

Finance is where SAP-adjacent automation compounds fastest: repetitive work drops while quality and speed rise together.


Every nearshoring provider is talking about AI. Here is what we actually point it at — requirements, test coverage and code review — and why that is a deliberate choice rather than a modest one.

We've moved into a house in the middle of Cluj-Napoca — 35+ desks, rooms to think in and rooms to argue in, and a garden that has already seen its first barbecue.
So what's next?
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