Yardstick Labrigorous software benchmarking
Document AI

Which document AI tool is actually most accurate?

We gave eight systems the same 72 real documents and asked each one for the same fields, then checked every answer by hand and published all of it. Five of the eight are dedicated extraction platforms; three are frontier AI models called directly. The documents are real invoices, bank statements, dense directories, rotated scans, and handwriting, in twelve languages. If a system couldn't read a file, it got a zero for that file. Nothing quietly drops out of an average here.

How to use this

Start wherever your question is

The ranking is the short answer. Everything below it exists so you can check it, or argue with it, using our own data.

The answer

Rankings

The accuracy leaderboard, a scorecard that adds price, product, data control and compliance, and the document types where the field separates.

See the rankings
The working

Evidence

All 72 documents, each tool's score on each one, and an explorer to open every file with its answer key and each extraction. The column averages are exactly the headline numbers.

Check every score
By workflow

Use Cases

The same documents grouped into the families buyers actually run, invoices, statements, payroll, healthcare, logistics, and dense registers, each scored on its own, with the leader per family.

See use cases
The opinion

Reviews

One review per system: what it is good at, where it falls down, what it costs, and what comes with it, ending in a weighted scorecard.

Read the reviews
Head to head

Compare

Any two systems side by side: accuracy by document type, price per page, product, and compliance, with a scorecard for each.

Compare two systems
Open evidence

Check every number yourself.

The documents, the per-file scores, and the failures are all published right here. Open any document with its answer key and every system's extraction, or download the replication kit and re-run the scorer yourself. Nothing here is a number you have to take on faith.

Explore the data