Seven AI agents. One human with the final say.

AI-Powered Data Curation

Your resource database.
Measurably better.

Every record is checked against the organization's own website. Dead links and wrong numbers are caught, duplicates are merged, missing fields are filled, and a human approves every change.

Every fact source-verified Human-approved Pushed back to your system of record
The DataClenze pipeline Curator-gated at every stage
01Intake
02Duplicate check
03Website verify
04Source extraction
05Approved updates
06Descriptions + categories
07Final quality audit
app.dataclenze.com/pipeline
Product screenshot - pipeline view
Drop the real curator pipeline board here: the seven stages with live record counts moving through each gate.
Curator review · proposed change

Meals on Wheels of Eastside

Home-delivered meals · Newark, DE
Silver
  • Phone confirmed on org websitesource
  • Service area matches program pagesource
  • No duplicate in your directorychecked
Why Silver: verified on the org's own site, not yet cross-confirmed on a second source.
What actually improves

A cleaner database, and you can see the difference.

DataClenze does not just tidy formatting. It clears out what is broken, merges what is duplicated, fills in what is missing, and grades every record so the gain is measured, not just claimed.

Dead links removed

Every website is checked. The ones that no longer load are flagged and cleared out of your directory.

Disconnected numbers caught

Phone numbers are confirmed against the organization's own site, so a caller does not reach a dead line.

Duplicates merged

Near-duplicate entries are resolved into one true record instead of three that disagree with each other.

Missing fields filled

Blank contact details, hours, and eligibility are filled in from the organization's own source page.

Every record graded

Each record earns a confidence grade you can sort, filter, and audit at a glance.

Gold Silver Bronze

Quality scored, not guessed

The app measures your data quality as a live score, so you can watch it climb as records get verified.

Data quality To confirmRecommend: your before and after quality score from a real run (the app shows this live).
The status quo

Directories go stale the day you finish checking them.

Manual phone-and-spreadsheet verification can't keep pace with a moving world. Numbers change, programs close, links die. By the time a team finishes a pass, the front of the list is already wrong again.

To confirm
Share of records that drift out of date within a year. Recommend: cite an I&R data-decay study or your own re-check rate.
To confirm
Weeks a team spends re-checking records a machine could read in minutes. Recommend: your baseline verification cycle length.
To confirm
Duplicate or near-duplicate entries hiding in a mature directory. Recommend: a dedup rate from a real cleanup run.
To confirm
Dead links and disconnected numbers still listed as active. Recommend: dead-link rate from a link-check pass.

The real cost isn't a messy spreadsheet. It's a caller in crisis, at 2am, dialing the shelter line you have on file and reaching a number that was disconnected months ago.

Stale data doesn't fail quietly. It fails the person who needed it most.
Why the usual fixes fail

Faster or cleaner. Most tools force the trade.

The two obvious answers each break in their own way. Understanding why is what makes the third answer worth building.

Bulk scrapers hallucinate

Point a mass-extraction tool at the open web and it will confidently overwrite good data with invented numbers, wrong addresses, and pages that belong to a different org entirely. Speed with no source is just faster mistakes.

Pure-manual can't keep pace

Calling every org by hand is accurate on the day it's done and out of date by the next. A human team simply can't re-verify thousands of records fast enough to stay ahead of a world that keeps changing under them.

Unverified AI is worse than stale

An AI that edits your records without proof doesn't just risk being wrong. It launders guesses into your system of record, where no one can tell what was verified and what was invented. Trust, once lost, is expensive to rebuild.

How DataClenze solves it

A pipeline that reads the world, then asks before it changes anything.

AI does the grinding across seven stages. Every proposed change stops at a human gate before it reaches your data. Fast where speed is safe, human where judgment matters.

Seven stages · one moving record Human gate at every step
Stage 01Intake gate
Stage 02Duplicate check gate
Stage 03Website verify gate
Stage 04Source extraction gate
Stage 05Approved updates gate
Stage 06Descriptions + categories gate
Stage 07Final quality audit gate
Screenshot slot
Curator review queue
The stage-by-stage board where a curator approves, edits, or holds each proposed change.
Screenshot slot
Source + provenance panel
A single record showing each proposed value beside the org page it was verified against.

Source-verified

Every proposed value cites the org's own website. If a change can't point to a real source, it doesn't get proposed. Blank beats invented, always.

No source, no change.

Human-gated

The AI proposes. A curator approves. Nothing reaches your data or your system of record without a person deciding it should. Every stage has a gate.

AI proposes, never applies.

Honest confidence

Bronze, Silver, and Gold tiers tell you exactly how well a record is verified, and why. Confidence is earned from real checks, never inflated to look good.

Tiers that say why, never puffed up.
Who it's for

Built for the people who keep the safety net accurate.

If your work depends on a directory being true when someone needs it, DataClenze was built for you.

211 & Information & Referral networks

When a caller is on the line, the number in front of your specialist has to be right. DataClenze keeps the whole directory current so no one gets routed to a dead end.

Aging & disability networks (ADRC)

Serving older adults and people with disabilities means program details and eligibility have to stay exact. Verification catches the changes before a client does.

State health & human services agencies

Statewide resource inventories that have to hold up to public scrutiny, with an audit trail behind every field.

Nonprofit & community resource directories

Small teams, big lists. Do the work of a re-verification department without hiring one.

United Ways & community foundations

The referral data you steward reflects on your name. Keep it accurate, and keep the proof of it.

Time + cost

Pay for judgment, not grinding.

DataClenze moves the slow, mechanical work to the machine and keeps your people on the decisions only a person should make.

Months of manual verification, compressed into days.

  • One curator does the work of a re-verification team, because the AI does the reading and the human does the ruling.
  • No more re-checking what hasn't changed. The pipeline surfaces only what actually moved.
  • Your team spends its hours approving good changes, not hunting for them.
To confirm
Less manual review time per verification cycle. Recommend: measure against a real baseline cycle before publishing a %.
To confirm
Records a single curator can keep current per week. Recommend: throughput from a real curator run.
To confirm
Cost per verified record vs. a manual phone pass. Recommend: model both costs, then state the ratio.
How you can trust it

Every change carries its receipts.

Trust isn't a promise on a marketing page. It's a mechanism you can inspect. Here's the mechanism.

Provenance on every field

Each verified value links back to the exact source it came from. Anyone can open a record and see where the fact was found, not just take it on faith.

Read-back on every push

When approved changes go to your system of record, DataClenze reads them back to confirm they actually landed. A success message is never mistaken for a saved record.

A full decision trail

Every proposal, approval, and edit is logged. Months later you can answer who changed what, when, and on what evidence, without reconstructing it from memory.

app.dataclenze.com/record/audit-trail
Screenshot slot - decision audit trail
A record's full history: every proposal, who approved it, when, and the source behind each change.
“

Reserved for a real customer quote. No testimonial appears here until a named customer has said it and approved it for use.

To confirm   Recommend: one line from a 211 or ADRC lead after a pilot.

Bring your directory
back to the truth.

See the seven-stage pipeline run on your own data, with a human gate at every step and a source behind every change.