Pileform: AI bookkeeping and VAT automation

Period-close used to take a finance team a full day. Pileform, our AI bookkeeping and VAT automation product, turns a quarter of receipts, invoices, and bank statements into reconciled, post-ready entries, and the close became about twenty minutes of review.

~20 min
Period-close became about twenty minutes of review, down from a full working day.
Sector
Finance / bookkeeping
Built by
Encelyte, end to end
Status
In production
Delivered
An AI document-capture and VAT-automation product

Our approach

We started where we always start, with an audit of where the time actually went. Most of it was not the judgement calls. It was the mechanical work of reading documents and matching them to entries. So we scoped the smallest system that would remove that work without taking the human out of the decisions that matter.

Then we built it for production from the first commit, not as a demo that reads clean test PDFs. Pileform had to handle messy, real-world invoices in multiple languages, apply tax logic that holds across jurisdictions, and leave a trail an auditor would accept. Because we run it ourselves, every rough edge surfaced on our own books before it reached anyone else's.

What we built

Pile in, form out

A quarter of receipts, invoices, and bank statements becomes reconciled, post-ready entries for Xero, QuickBooks, and BTMS.

Reads real-world documents

It captures line items, dates, amounts, and counterparties from messy invoices across multiple languages, not just clean test files.

Cross-border VAT

It applies the right VAT across jurisdictions, so books that span more than one country close together in a single workflow.

Your books at a glance

One dashboard shows what is captured, what still needs review, and how long the pile took to clear.

Your books at a glance
The workspace dashboard: receipts captured, entries posted, what still needs review, and the average time to clear the pile.

Reviewed, not just read

Every entry arrives with the model's reasoning and a confidence score, so the team checks only the few that need a human eye.

Reviewed, not just read
The review queue: each entry carries the model's confidence score and its reasoning, so only the uncertain ones need a second look.

Traced to the source

Each line ties back to the original invoice, one click away. Nothing is taken on trust, and the output stands up to an audit.

Traced to the source
The same entry with its source invoice open alongside it, so every figure is one click from the document it came from.

Before and after

Before

Period-close is a tax on every finance team. A full day disappears into sorting documents, keying line items by hand, reconciling against the bank, and applying the right VAT rule for each jurisdiction. It holds until the volume grows or the books touch more than one country. Then it stops scaling.

We had the same problem ourselves. So we built the tool we wanted, and held it to the standard we would hold any client build to.

After

The work that used to fill a day is now a short review of the few entries the system flags. The team spends its time on the judgement calls, not the data entry.

Every figure on the return traces back to the document it came from, so the close is faster and the audit trail is stronger at the same time.

Period-close became about twenty minutes of review, down from a full working day.

Result~20 min

The stack

Capture
Document AI pipeline (OCR + model layer)
Integrations
Xero, QuickBooks, BTMS
Domain
Cross-border VAT automation

Have a problem like this?

Pileform exists because we got tired of doing period-close by hand. Most teams have a Pileform-shaped problem somewhere: a repetitive, high-stakes process that should be software. If that sounds familiar, tell us about it.

See Pileform