Methodology

From fragmented sources to usable vertical intelligence.

Every record runs the same pipeline. That's why coverage compounds across verticals — and why our signals stay explainable.

The pipeline

Seven stages, every record.

01
Source
02
Match
03
Normalize
04
Enrich
05
Verify
06
Monitor
07
Deliver
How it works

Source. We collect from public and licensed sources appropriate to each vertical — for GLP-1 clinics, that includes Google Maps, the NPI Registry, LegitScript, and FDA records. Each field carries its source.

Match & de-duplicate. Records that refer to the same real-world business are resolved into a single canonical entity with a stable identifier — handling chains, name variations, and address changes.

Normalize. Names, addresses, and categories are standardized into one model, and locations are geocoded so records are comparable across sources and verticals.

Enrich. We add vertical-specific attributes — pet service types and profile completeness; GLP-1 brands, published pricing, and verification status.

Verify. Where an authoritative check exists, we attach it as a source-linked signal: LegitScript certification, NPI matches against the CMS registry, FDA warning-letter flags, and verified phone / website / location.

Monitor. Records are re-checked on a cadence set per vertical — GLP-1 pricing is refreshed daily. Changes are tracked so the data stays current rather than going stale.

Deliver. Clean records ship as CSV, Excel, Google Sheets, Parquet, or scheduled reports — scoped to the attributes, geography, and refresh cadence you need.

Scoring

Explainable signals, kept honest.

Our trust and transparency signals are built from explainable inputs — for GLP-1 clinics: LegitScript certification, FDA warning status, Google rating, price transparency, and clinical depth; for pet care: rating, review volume, and profile completeness.

Commercial placement never changes an objective signal

Businesses can claim profiles and pay for optional featured placement in our applications. Paid placement is labeled as such and is kept separate from objective data signals — it does not raise a trust, transparency, or verification score.

What we don't claim

Coverage is wide but not exhaustive, and some fields are more complete than others. We publish our known limits on the Coverage page, and we don't describe data as "real-time" or "fully verified" when it isn't. If you find an error, our Data Corrections process is open to anyone.

Want to see the coverage behind the method? View coverage →

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