Every check by name, in plain words. Method v1.0, 2026-09-11. The version is printed on the cover of every exhibit; the same files, the same version and the same edits produce the same findings hash.
Every note is a review signal. A note is weighted high only where the checks have shown, on real files, that no ordinary explanation remains; everything else is marked review. A new check ships at review weight and earns a higher weight only after real matters show where the line sits.
Docuritas proves the numbers and flags what broke a check. What stays with the examiner:
A procedure an opposing expert can follow and a sponsoring witness can testify to having followed. Two hashes are involved and they claim different things. The findings hash, printed on the cover and in the footer of every page, is computed over the input file hashes and their declared sources, every row as exported, the method version and the reviewer's screen parameters — never the matter name, the reviewer or a file's name; it is the same on any computer. The file hash is SHA-256 of the exhibit PDF itself; it is the same only on the same software build, with the same preparation date (printed in UTC) and in the same form (the exhibit for filing, or the working paper), all three of which are printed on the cover — the preparation date is deliberately outside the findings hash, so a rerun on a later date reproduces every figure without pretending it was prepared that day.
shasum -a 256 exhibit.pdf and compare with the file hash shown on screen when the exhibit was downloaded. A match proves the file is the one produced.Where a page was read by OCR, the OCR engine and its training data are part of the findings hash, because a different reader of an image is a different engine. Reruns pinned to a prior method version are available on request. There is no lookup service for hashes and there never will be: confirming a hash would mean keeping a record that the matter existed, and nothing is kept.
Not a position on a technology; a specific failure mode. A language model produces plausible continuations, and a reconciled statement is more plausible than an unreconciled one. On statements that tie cleanly it performs well, and those are the ones nobody needed checked. On the statement whose closing balance is off by 4,200.00, its bias is to smooth the discrepancy into something that reconciles, confidently and silently. The error concentrates on exactly the cases this method exists to find, and no prompt or second model fixes that. Try it on the synthetic sample, never on a client's file: ask any assistant to verify the opening and closing balances and compare with the exhibit.
The rule that follows: a model may propose, only arithmetic may dispose. Nothing that computes, adjusts, infers or reconciles a number in the exhibit, the register, the proof or the findings hash may come from a model. Today nothing in the pipeline uses one at all.
The version is printed on the cover of every exhibit. A check added, removed or re-weighted is listed here with its date, so an exhibit can be read against the method that produced it.
The engine is scored on a labelled corpus of altered and genuine statement sets, kept as the regression suite that gates every release. Cases the method does not resolve are listed in the exhibit as not checked.