We automate the reconciliation and the account questions that are slowing your finance operation down. Your compliance position does not move.
Hitasoft builds AI automation for fintech and financial services companies. Transactions get categorised and matched against the ledger as they arrive, and invoices and receipts become database rows without anybody retyping them. Models run with retention switched off, and open weight models can run on servers you control.
Finance teams scale until the manual work becomes the job. The choice is another pair of hands, or asking your one technical person to build reconciliation logic instead of the product. Neither one is a good trade.
Multi-user expense splitting and debt calculation is fiddly logic, and it goes wrong very quietly. Two systems disagree by a small amount, and nobody notices until somebody closes the month.
Invoices and KYC documents turn up as PDFs and photographs. Somebody opens each one and types what it says into a system that could have read it itself.
Tier one account queries repeat all day and every one of them still needs a person. That person costs the same as the hard question waiting behind it in the queue.
Transactions get categorised as they arrive, and the ledger updates with no spreadsheet import at all. Where a balance is split between several people, a shared household budget or a trip, each share recalculates on every entry. Whatever does not reconcile goes to a person, and the reason is attached to it.
Vision capable models read invoices and receipts and write them into your database as structured rows. A person reviews only what the model flagged as uncertain, which is a fraction of the pile.
An agent answers tier one account questions from your own knowledge base rather than from the internet. Anything outside what it has been given goes to your team, not to a guess.
Five steps. A person still sits at exactly one of them. That is the honest version of it, and it is the one worth building around.
A PDF or a photograph lands in the inbox.
A vision model lifts the supplier and the amounts.
The entry is matched against your ledger.
A person reviews only what came back uncertain.
Human checkpointThe row is written, with the reasoning logged.
The same work, pointed at other corners of the sector.
Financial records cannot leak, and a model that has seen them is a record of them. Every integration is built so that your records stay inside the systems you already control.
Integrations run against business tier endpoints with retention turned off, so your inputs never enter a training set. Somebody has to switch that on, and we check it.
Open weight models can be deployed onto servers you already own, on AWS or on your own hardware. The records never leave the hardware you already control.
Every automated decision and every extracted figure is written to a log in plain language. An auditor who asks why a transaction was categorised that way gets a straight answer.
We build the middleware that makes your current tools intelligent. These are the systems finance teams bring us, and your own stack does not have to be on the list.
The integration reads the transaction feed through your banking API and categorises each line with a model. Every member's balance in the shared ledger recalculates from there. Nobody types a number in.
Consumer ChatGPT is not safe for financial records, and it is not what we build on. A business tier endpoint with retention switched off processes the data and then keeps nothing at all. Open weight models can run on hardware you own.
Three weeks for a single workflow, audit to live. The audit comes first and it is where the reconciliation rules get written down, because a model cannot infer a policy nobody has stated.
Not from a model guessing, because the agent reads the balance from your database rather than generating it. Anything it cannot answer from your own records gets handed to a person on your team.
Both, and they are different projects. This page is about automating what you already run. A financial product built from nothing is an MVP, and that has its own page under services.
No. The automation sits beside what you run and talks to it through the API it already exposes. Your team opens the same books on Monday.
The audit puts a number on it before you commit, and there is no open ended discovery phase. You pay for the middleware and the API work rather than for a new platform.
Data entry, answering the same tickets, chasing numbers between systems. We automate the parts that repeat. Your team keeps the parts that need judgement.
