Best data extraction software for invoices and accounts payable (2026)

Solutions by usage profile

This list is not a ranking: each group describes a company profile and the solutions designed for it. For each competitor we report who it is a good choice for and its pricing model, as stated on the official pages consulted on 25 September 2026.

FatturaPA/SdI XML, line items and matching with order and delivery note

For an Italian SME three criteria matter more than the others: reading the e-invoice (FatturaPA XML from the Exchange System, SdI), extracting line items and not just the header, and matching the invoice with the order and delivery note (three-way matching). We report what is stated on the pages consulted.

"Not stated on the pages consulted" means the feature is not described in the sources listed under the matrix, not that the product lacks it: always check with the vendor.

Data extraction software vs template OCR vs manual data entry

Before comparing vendors, it helps to compare approaches. Behind every product on this page sits one of three ways of getting data out of a document and into the ERP: people typing it in (in-house or outsourced), OCR driven by a template for each layout, or extraction by a large language model (LLM) that reads the document the way a person would. The table compares the three on the points that decide the real workload.

Data Alchemy belongs to the third approach: each document model is a JSON structure of the fields to extract plus reading instructions in natural language, read by the AI engine you choose for that model. With external fields and remote validation (Business and Enterprise) the extracted values are checked against ERP data before they are written.

How much does invoice data extraction software cost

The matrix shows each solution's pricing model, with figures only where the vendor publishes them. There are five recurring models, and they are worth comparing at the same volumes and pages per document.

In the comparison, also account for the items that are not on the price list: ERP configuration and integration, operator training, maintenance of templates and rules, and the residual time spent checking exceptions.

How accurate is AI invoice data extraction

Data Alchemy states 99.8% accuracy (measured with Claude; no figure is published for the other engines). It assigns a single AI engine to each document model — Claude by default, GPT, Data Alchemy AI (the proprietary model, on its own servers and GPUs in Italy) or a compatible model through the European providers Scaleway and Regolo.ai — with no templates or per-layout training, and with external fields and remote validation (Business and Enterprise) it compares extracted values with ERP data.

We do not report competitors' accuracy percentages: without a shared public methodology the numbers are not comparable. The accuracy that matters is post-validation, measured on the header and line items of your real documents.

How to test data extraction software on your own documents

A trial is only useful if every vendor is tested the same way. This five-step protocol takes a few days and gives you numbers you can compare across products, including ours.

1. 1.Build a sample that looks like a real month: invoices from your top suppliers and from occasional ones, multi-page documents, scans and photos, FatturaPA XML next to PDF courtesy copies, and the delivery notes and orders they refer to.
2. 2.Write down the fields that matter before you start: header (supplier, VAT number, number, date, totals) and line items (code, description, quantity, price, VAT rate). A tool that reads totals but misses lines will still leave the typing to your team.
3. 3.Measure field by field after validation, not document by document before it: count the fields that reach the ERP correct, the ones flagged as exceptions and the ones that are wrong without being flagged. The last group is the one that costs money.
4. 4.Time the exceptions: how long an operator needs to understand and fix each flagged document. This, not the extraction time, is the residual workload you will pay for every month.
5. 5.Test the last step too: write the validated data into a test company of your ERP and check that suppliers, items and order references match. Extraction that stops at an export file is not yet automation.

Run the same sample through every candidate and compare the results side by side. You can start with a call and a demo on your own documents.

When Data Alchemy isn't the right fit

There are real cases where another solution on this page is a better fit. Better to say so up front.

Continue the comparison