Healthcare entity resolution

Match messy provider data to verified NPIs.

Upload a spreadsheet of providers or organizations. NPI Finder matches each row against the federal NPPES registry and public web evidence, then returns confidence-rated NPIs with the sources to prove them.

$5 of credit on signup. Five rows free, no card required.

NPPES-first

Discovery starts with the federal NPPES registry.

Name-gated

Location signals support a name match but can't replace it.

Auditable

Confidence, candidates, and sources travel with every row.

Resolution ledger

providers_q2.csv

RunningComplete

5

rows

8

NPPES verifies

12

source URLs

ProviderResult
  • Sarah K. Lindqvist, MD

    Family Medicine · Portland, OR

    Sarah K. Lindqvist, MD

    High

    LINDQVIST, SARAH K · street match

    1487362091

  • Cascade Heart & Vascular

    Cardiology group · Bend, OR

    Cascade Heart & Vascular

    High

    CASCADE HEART AND VASCULAR LLC · street match

    1663984528

  • Dr. Mike Okafor

    Internal Medicine · Spokane, WA

    Dr. Mike Okafor

    High

    OKAFOR, MICHAEL · nickname expanded

    1248573903

  • Riverstone Pediatrics

    Pediatrics · Boise, ID

    Riverstone Pediatrics

    Medium

    Former name: LAKEVIEW CHILDREN'S CLINIC · ZIP match

    1582603472

  • Summit Care Clinic

    Urgent care · Reno, NV

    Summit Care Clinic

    No match

    name gate failed · 3 candidates rejected

5 of 5 completed · $5.00 chargedExport CSV
Fictional demo data. NPI format follows the real check-digit rule.registry + web + verify

Operating model

Built for provider files that need a defensible answer.

NPI Finder is intentionally narrow: it resolves provider and organization rows, verifies candidate identifiers, and returns the trail behind the match.

Signal

Cited

completed rows include the matched registry record, reasoning, candidate context, and source URLs

NPPES-first

healthcare entity matching starts with the federal registry before escalating to public web evidence

$1

per completed row run, charged up front. System failures are credited back to your balance automatically

50k

rows per uploaded table in the app, with controlled parallel runs and streaming results

Built for

Healthcare entity resolutionNPI entity resolutionClaims & billing filesReferral networksProvider directoriesCRM enrichmentCredentialing prepRecruiting lists

Explore the resolution problem

Four ways teams describe the same provider data work.

Whether you call it healthcare entity resolution, NPI entity resolution, or bulk NPI lookup, the job is the same: match messy rows to verified provider identities with evidence.

The resolution problem

Entity resolution is where NPI cleanup gets expensive.

01

Claims bounce

A wrong NPI turns into denials, resubmissions, and follow-up work that costs far more than the original typo.

02

Directories go stale

Providers move, change names, rebrand, and merge. A spreadsheet that was right last quarter won't tell you which rows have changed since.

03

Lookup doesn't resolve identity

Manual NPPES searches take minutes per row and struggle with nicknames, DBAs, and misspellings. Fuzzy matching is faster, but it can't tell you whether a near-match is actually the same entity.

The method

NPI entity resolution, row by row.

NPI Finder runs a research process for each row across registry records, public web evidence, source pages, and NPPES verification. The evidence behind every answer is recorded before it's submitted.

  1. 01

    Discover

    Registry-first search of NPPES with nickname expansion, former names, DBAs, and wildcards. When the registry can't see a row (misspellings, marketing names, a bare domain), the agent escalates to the open web.

  2. 02

    Verify

    Candidate NPIs are screened with the NPI check-digit algorithm and checked against the federal registry by 10-digit number. If a fallback cannot be verified, it is capped low and flagged for review.

  3. 03

    Match

    The name-identity gate: the registered name must plausibly denote your entity. Address, ZIP, and phone corroborate a name match but never substitute for one, so a different practice at the same address gets rejected.

  4. 04

    Show its work

    Each completed row returns the chosen NPI, a confidence rating, the matched registry record, candidates considered, and the URLs it relied on, so the decision can be audited later.

row 3 · Dr. Mike Okafor — agent traceresolved
  • nppes_search“okafor, michael” · Spokane, WA3 candidates
  • web_search“Dr. Mike Okafor Spokane internal medicine”nickname evidence
  • web_fetchspokane-internalmed.com/providersaddress confirmed
  • nppes_verify1248573903✓ check digit · ✓ registry
  • submit_answername gate passed · street matchconfidence: high

Investigation path: registry discovery · public web corroboration · NPPES verification · confidence-rated answer or no-match.

What you get

Built for files where provider identity matters.

01

Streaming results

Rows land in the grid the moment they resolve, so you can review early results while the rest of the batch runs.

02

Graded confidence

High, medium, or low, graded by how the registry record corroborates your data across street, ZIP, city, state, and phone.

03

Explained no-matches

When the name-identity gate fails, the row comes back as a no-match with the reasoning and sources from the investigation, rather than the nearest plausible-looking record.

04

One-click reruns

Rerun a single row, rerun everything below high confidence, or rerun the whole batch. Each rerun is a fresh investigation.

05

Audit-ready export

One CSV: your original columns joined with the NPI, matched name and address, confidence, reasoning, candidates, and source URLs.

06

Individuals & organizations

Type 1 and Type 2, with an enforced filter so an organization is never resolved to a person's NPI or vice versa.

Validated claims

NPI facts you can check at the source.

Public NPI facts on this site link to the CMS and HHS documents they come from. Product claims describe how the app actually behaves, including its review limits.

Pricing

Simple commercial terms for messy provider files.

Per-row pricing keeps the cost tied to completed work. You can review a small batch, top up for a larger cleanup, and export only the evidence-backed results you want to move downstream.

$1.00

per completed row run

Completed no-matches stay charged because the investigation happened.

$5.00

welcome credit on signup

Enough to run five rows before adding a card.

10%

bonus credit on top-ups of $100+

System failures and cancelled unfinished rows are credited back automatically.

Start with your file

Stop reconciling healthcare entities by hand.

Your first five rows are on us. Upload the provider file you have now and review the evidence before it moves downstream.