For dirty data with a paper trail

Everyone checks AI with more AI. We check it against the source.

ZH checks every record against its source document, deterministically, and returns a verdict and a receipt. It checks again when AI reasons over those records, and once more before anything goes to your clients. Failures go back for repair; what can't be repaired goes to a person. It runs inside your environment. Your production data stays in your environment.

Request a demoSee how it works

More than 11.6 million verification runs in production as of September 17, 2026.

The problem

Dirty data has a cause. Nobody checked it against the source.

01

A field that doesn't match the filing it was keyed from.

02

A record nobody can trace back to a document.

03

A review team checking every row by hand, and never catching up.

Cleaning tools fix formats and duplicates. They don't know whether the record is true to its source. ZH does one thing: it checks.

Unstructured in, structured out

Messy documents in. Structured records out, every field tied to its page.

Most dirty data starts as paper: run sheets, scanned filings, PDFs, spreadsheets nobody trusts. The model reads them and proposes a structured record. ZH checks every field against the page it came from before the record enters your store. What it can't trace, it flags for a person.

INSTRUMENT NO. 1987-004412PAGE 3 OF 7
MINERAL DEED

KNOW ALL MEN BY THESE PRESENTS, that R. A. HOLLOWAY, Grantor, for and in consideration of ten dollars, does hereby grant and convey unto EASTFIELD ROYALTY CO., Grantee,

an undivided one-half (1/2) interest in the oil, gas and other minerals in and under the following lands:

Section 14, Block 3, A-221, containing 160 acres more or less.

Recorded March 9, 1987, Book 412, Page 88.

Reservations: (illegible)

Structured recordSource: Instr. 1987-004412
Grantor
R. A. Hollowayp. 3, line 1
Grantee
Eastfield Royalty Co.p. 3, line 2
Interest
1/2 mineralp. 3, line 4
Tract
Sec. 14, Blk 3, A-221p. 3, line 5
Recorded
1987-03-09, Bk 412 Pg 88p. 3, line 6
Reservations
Not tracedUNSUPPORTED

Flagged for a person: the reservation clause could not be read from the source page.

Illustrative document. Names and instrument numbers are fictional.

How it works

Three checkpoints. One engine.

Clean data in, checked when AI interprets it, checked once more before it reaches your clients. A failed claim goes back to the model, up to five passes. What it still cannot ground lands with a person as a named exception. ZH never writes the fix.

Step 1 of 6 · The record as it arrived

Step 1 of 6: The record as it arrived. This is what was ingested. Nobody has checked it yet.

Grant record

Community Health Workforce Grants

Funder
State Department of Health
Program
Community Health Workforce Grants
Award ceiling
$250,000
Deadline
January 15, 2027
Geography
Rural counties
Eligibility
Licensed clinics

Not yet checked

Source document · page 2

Notice of funding opportunity

The State Department of Health invites applications for Community Health Workforce Grants.

Awards will not exceed $150,000 per applicant.

Applications are due January 15, 2027. Applicants must serve residents of the state's rural counties.

Eligible entities are defined in Appendix B.

This is what was ingested. Nobody has checked it yet.

Eight outcomesVERIFIEDOUTDATEDNOT_REVIEWEDUNSUPPORTEDMISSTATEDCONFLICTING_EVIDENCECONTRADICTEDFABRICATED

Illustrative walkthrough. All programs, records, claims, and receipt values in this example are fictional. No live customer data is displayed.

What you get

A verdict and a receipt for every record

One of eight outcomes

Per claim: VERIFIED, FABRICATED, MISSTATED, CONTRADICTED, CONFLICTING_EVIDENCE, OUTDATED, UNSUPPORTED, NOT_REVIEWED.

A receipt per decision

What was checked, against which document, when. SHA-256 audit chain, Ed25519 signed.

A repair queue

What the model fixed, what it couldn't, and the exact rows a person needs to look at.

Three checkpoints, one engine

Intake, interpretation, delivery. Fail closed at each. Anything ZH can't trace to a source is not passed through as clean.

Proof

We built GrantAuthority this way

Brightstead built GrantAuthority with ZH at intake, not bolted on after. Built in months, with ZH checking every record as it loaded.

560M

records

2.19M

foundations mapped

6.3M

historical grants

11.6M+

verification runs in production

GrantAuthority counts as of September 17, 2026.

Deployment

Runs where your data lives

Kubernetes deployment in your environment, or the API behind your firewall.
Pairs with the language model you already run. ZH is the deterministic check; the model proposes, ZH decides.
No Brightstead hosting required. Your production records stay in your environment.
Patent applications filed.
Plan your security review. We review data flows, access controls, audit receipts, and key management with your team during pilot planning.

How to buy

A paid pilot first, in your environment

One record set, one team, one quarter. Priced per record with a platform minimum. You keep everything ZH produces.
Runs on your platform. Nothing is hosted by Brightstead unless you ask for it.
Receipts your auditor, your Inspector General, or your regulator can replay.
Vendor facts

Brightstead Technologies, Inc., Austin, Texas.

Ask us for current vendor registration and procurement details.

Who it's for

Government

State and federal agencies whose records drive payments, leases, benefits, eligibility or disaster response.

Enterprise

Title underwriters, banks, insurers, grantmakers and any large institution whose records have to match the documents behind them and survive an audit.

See it on records like yours

Tell us about the record set. We aim to reply within two business days. No file upload needed.

A short description is enough. Please leave out confidential or personal records.

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Prefer email? getcleandata@brightstead.com