01 / EVIDENCE
Evidence before confidence
Matched fields, score components, source freshness, and the official notice are visible before the numeric score.
Review-ready evidence
A recall match should showwhy it matched.
An API and CSV workbench that turns messy product rows into explainable recall candidates, visible source coverage, and a safer human-review queue.
- Built for
- Resale marketplaces, consignment teams, and catalog developers
- Domain-ready
- recalllens.apptillion.com
Comparison plateCPSC candidate 1 of 1
Specimen A · your row
brandFisher-Price
product typeinfant swing
modelABC123
lot / date code(not supplied)
Specimen B · recall notice
brandFisher-Price
productinfant cradle swing
model familyABC123-*
affected lots0417-0921
2 exact · 1 partial · 1 missingscore 86
Review queue · live preview
Evidence first. The score is the consequence.
Illustrative sample row. A no-match result never means an item is safe or not recalled.
sample
Every candidate returns its matched fields before its score.
Why the evidence leads
Less anxiety. More visible progress.
The competitors prove the job exists. RecallLens improves the moment between row and decision: matched fields and source freshness are visible before the score, and a reviewer always has a next action.
02 / EVIDENCE
A humane review queue
Reviewers see the missing field to request, not a frightening red badge with no route to resolution.
03 / EVIDENCE
Cheaper public-source architecture
Local normalized indexes cover routine matching; official APIs and live links remain the verification layer.
Match pipeline
One complete path from row to next action.
- STAGE 01
Normalize the row
Clean brands, titles, model numbers, UPCs, lots, and dates without erasing the original input.
- STAGE 02
Show candidate evidence
Return field-level reasons, source state, and which identifiers are still missing.
- STAGE 03
Route the next action
Continue, request a model or lot, or require a reviewer to open the official recall notice.
Pricing without make-believe
Cheaper per call, because the architecture is cheaper.
RecallLens proposes $9/5,000 and $29/25,000 calls: roughly 76% and 78% lower per call at the compared tiers.
PlanPriceIncludedNotes
Explore
$01,000 calls/monthAPI keys, explainable matches, source state, and a 100-row CSV scan.
Join early access
Review queue
$2925,000 calls/monthAbout 78% less per call than CatalogRecall Developer, plus batch review.
Join early access
†Best first paid job — the tier most integrations start on.
Compared with:CatalogRecall: $19/2,500 calls and $79/15,000 calls
Pricing-stage early access
Bring a real RecallLens use case.
This is a preview, not a completed paid service. Join early access and tell us what a useful first release must handle.
RecallLens performs automated matching against connected public sources. A no-match result never means an item is safe or not recalled.
The trust boundary
Scope of review
RecallLens performs automated matching against connected public sources. A no-match result never means an item is safe or not recalled.
Sources reviewed July 24, 2026