RealtimeData
Finance and back office automation

Finance automation: invoices, accounts payable and bookkeeping with AI

Invoice automation, accounts payable automation and AI for accounting that an auditor can follow: every figure keeps the document line it came from, every posting keeps who approved it, and the arithmetic is code, not a guess.

invoice automationaccounts payable automationai bookkeepingai for accountingdocument automationdata entry automation
Start the free diagnostic Talk to the architect

Why most of it never goes live

Finance is where a made up number costs the most. An AI that reads an invoice and confidently transposes two digits, or posts to the wrong period, creates work for the accountant and a finding for the auditor. Back office automation only pays when every number can be traced back and every posting can be explained.

The fix is the same five phase method behind every one of the twenty-seven systems on the work page: someone owns the outcome, the data is found, the definitions are agreed, the real process leaves a record, and only then does anything ship. The free AI readiness diagnostic tells you which phase you are in.

What we build for this

Invoice and document processing

Invoices, receipts, statements and contracts read into structured records with the source line kept beside every field. Amounts are extracted, then recomputed and checked, never trusted from a single read.

Posting and reconciliation

The agentic operations platform reconciles deposits against a ledger every day and posts them behind gates that fail closed, with two ledgers checked against each other.

Numbers computed, not described

In the tax and accounting canon, the euro impact of each legal lever is computed arithmetically rather than described by a model, beside a citation aware corpus of the law. The same rule applies to every finance agent we build.

Audit readiness by construction

Every automated posting carries its source document, the rule applied, the confidence and the approver. See AI governance and audit readiness.

How it stays trustworthy

Grounded, trustworthy AI is not a slogan here. It is five rules every agent we ship has to pass.

Cites its sourcesEvery answer an agent gives points at the document, record or rule it came from. If it cannot cite it, it does not say it.
Refuses to inventWhen the data is missing or the question is outside what it knows, the agent says so and stops, instead of producing a confident guess.
Stops and asks a personAnything uncertain, unusual or expensive goes to a named person with the evidence attached. The agent never acts on a hunch.
Leaves an evidence trailEvery step records the source, the definition used, the confidence, who approved it and the outcome, so a reviewer or an auditor can see why it acted.
Runs inside your perimeterModels and data run on hardware we own or on yours. Client data does not have to leave the building to be worked on.

The services behind it

From the seven AI consultancy services offered from Barcelona and Alanya, these are the ones this work draws on.

Questions people ask

Does it work with our accounting software?

It works beside it. Extracted and checked records are posted through the software's API or import, and the software stays the system of record.

How accurate is the extraction?

Every amount is read, recomputed and cross checked, and anything that does not reconcile goes to a person with the document attached. Accuracy is measured on your documents during the free diagnostic phase, not claimed in advance.

Is it GDPR compliant?

Data governance is part of the build: who owns each dataset, where it lives, what it is used for, and that it stays inside your perimeter. The sector regimes that apply to you are written into the specification.

Can an auditor follow it?

That is the point. Each posting can show the source, the rule, the approver and the time. Systems that can show a reviewer why they answered the way they did are what we build.