Attestiq

Use case · Instant payments

Prove every chargeback response your AI files.

An instant-payments processor moves money for lending, payroll, gaming, and wallet programs. When a card-funded transfer is charged back, an AI agent drafts the response to the network. Attestiq checks every fact in it — including every piece of fraud evidence it claims — before it is filed.

The error that costs the most

A draft that is right about everything but one thing.

AVS match, CVV2, three prior undisputed transactions — all true. Then one more sentence claims a device match the risk signals don't show. Filed, that sentence misrepresents the case to the network. Attestiq checks every claimed piece of evidence against the case record and fails the draft.

disputes.representment · Visa 10.4

Fail

Compelling evidence: The billing address returned an AVS full match. The CVV2 was verified at the time of the transaction. Transaction history shows 3 previous undisputed transactions with the same card. The transfer was initiated from the same device used for the account's earlier activity.

criticalFACT.UNSUPPORTED_CLAIM

The document claims a device match to prior activity, but the evidence records do not include it.

case evidence: avs_full_match, cvv2_match, prior_undisputed_transactions

Before and after

Analysts review the 11% that need it, not all of it.

Check facts against the caseAn analyst re-reads every draft: about 30 minutesCode checks every claim in milliseconds; 89% of drafts pass with evidence attached
Catch invented evidenceDepends on someone noticingEvery claimed 3DS, AVS, CVV2, ANI, device, or history fact checked against the risk signals
Filing windowTracked in a queue or spreadsheetComputed per network from the chargeback date; late drafts held
Fix an errorFind it, then rewriteThe held draft opens at the exact sentence, with the rule and the record
Evidence for the examinerAssembled by hand, on requestA signed record per finding; the attestation pack in one click

Rehearsal results · synthetic data

1,000

synthetic AI-drafted chargeback responses in the rehearsal

93.4%

of drafts with an injected error caught; every miss is a case the model tier is designed for

0%

of clean drafts held for review

~1 ms

per draft in deterministic mode

Measured on a synthetic quarter of chargebacks with injected, labeled errors. Real agent output is harder; a pilot measures accuracy on your own historical drafts, with your analyst labeling the findings.

Value model

Put in your numbers.

Same formula we use in the pilot readout. Change any input.

Modeled annual value

$987,307

Analyst time per draft
30 → 9.4 min
Analyst hours freed
17,203 h (9.6 FTE)
Labor value
$860,167
Errors newly caught before filing
2,825
Chargebacks recovered
$127,141

A model, not a result. Hold rate (11.3%), error rate (12.1%), and catch rate (93.4%) come from a synthetic 1,000-draft rehearsal; a pilot replaces them with rates measured on your own drafts. Credits only half of the errors caught, assuming your analysts catch the rest today.

Security and privacy

Send the minimum. Prove everything.

The drafting agent sends the draft plus three records: the transaction, the chargeback, and the evidence list. No card numbers, no SSNs, no addresses.

  • Card numbers are rejected at the API; none are stored
  • The draft itself is never stored, only its SHA-256 and a redacted copy
  • Names and personal data are redacted before storage or any model call
  • Every finding is signed; the audit log is a hash chain examiners can recompute
  • Deployable in our AWS, a dedicated VPC, or your own AWS account

Eight weeks to an attested AI workload.

A fixed-fee pilot on one workload: an eval report on your historical outputs and an attestation draft for your compliance team.