TwoHands

Two Hands catches typing errors in digitized handwritten forms: Gemma-4-31B-IT on the AMD Token Factory reads every number twice, as digits and as words, and the form's own arithmetic decides what is accepted. On 1,270 real Mexican tally sheets it found 49 typing errors in the official records, each confirmed by the certified count. How it works: names and signatures are blacked out; Gemma reads each number; plain arithmetic checks it (words must match digits, rows must add up to the total). If everything holds, the form is accepted. If not, only that number goes to a person, with its photo. Every finding gets a verifiable receipt. Results (Mexico, 2024): - 91.6% field match on Baja California Sur's sheets vs 62.84% for the Google Document AI reading the state bought (same metric; ours on a random 300, theirs on all 2,020). - Caught 27 of 28 errors the certified count reveals (pre-registered); 0 wrong in 484 accepted fields on 100 fresh forms. - In a 300-sheet sample audit, the auditor reviews only 267 disputed numbers of 6,358 (4%). Business: first buyers: INE, Mexico's 32 state electoral institutes and their auditors, before June 2027's concurrent elections. $1 per sheet proposed, about 0.5% of what one state paid to run its count; first step a paid pilot. The check is the form's own arithmetic, so it isn't tied to elections: it already works on UK rainfall ledgers from 1850-1960 (same model, no retraining). Next buyers: election bodies in 7 more countries that publish their tally sheets, health ministries' data-quality teams checking DHIS2 clinic reports in 70+ countries, and archives digitizing handwritten records. Why Gemma: same 300 sheets and checks, 1.8x the forms Qwen accepts, 4.6x cheaper, 2.8x faster; a whole state (982 sheets) for $0.14. Evolus: each strong finding opens a case; an agent on Gemma writes it up, a script scores the evidence, the auditor decides. All numbers re-derive from public data (make eval). Built solo.