One rate-intelligence estate.Every payer, every code,every market.
41 federal, commercial, and geographic datasets, fused into one normalized graph — joined on NPI, CPT, and geography — that scores any provider's rate against its true local peers and turns every rate into one comparable number: % of Medicare.
See your RateScore and one documented reimbursement opportunity free, no PHI required. Your structure depends on your NPIs, payer mix, and the opportunity in your own data, so we price it with you on a short call.
Scope of the public estate we continuously index toward — not a live row count. Coverage by code, payer, and market is disclosed on every result. See our honesty standard →
Every buyer and every competitor speaks in "% of Medicare" — but nobody had a clean Medicare denominator for the down-market layer.
A locality-correct Medicare engine.
Work / PE / MP RVUs × locality GPCIs × the conversion factor → a locality-correct Medicare allowed amount for every code, served by the medicare_allowed() engine.
The moat is integration,
not raw size.
Nine data domains in one normalized graph — commercial TiC, out-of-network, Medicare benchmarks, drug pricing, hospital charges, the provider/group graph, geography, quality, and discovery — joined on NPI, CPT, and market. Every other vendor brings two to four, siloed by delivery format. We normalize 41 datasets to the same 110 GPCI localities on a public-data cost base, so a single CPT speaks as a % of Medicare, a commercial rate, a hospital charge, and a Medicaid fee at once.
Local-peer scoring is the payoff of that fusion — and it is being hardened from national to true metro-level accuracy. We lead with nine domains in one graph (true today) and frame local-peer scoring as the engine that breadth makes possible, not a production-proven metro number.
Browse the data backbone.
One normalized graph. Filter by what you care about — domain, what's live, the tool it powers, the audience it serves.
What the estate powers.
Every dataset above feeds a live surface. The data doesn't sit in a warehouse — it scores rates, builds memos, and maps markets.
Built for the people who use the data.
You already suspect you're underpaid on some codes and fine on others — you just can't prove which, or by how much. We turn the public rate estate into your answer: for each of your codes, your rate next to your local same-specialty peer set, expressed as a percent of Medicare, with the gap quantified and the target documented. Documented reimbursement opportunity is modeled, not guaranteed.
The moat is a compounding public-data estate: 41 federal, commercial, and geographic datasets fused into one normalized graph, refreshed on a cadence, with a per-NPI local-peer engine no incumbent offers down-market. The architecture keeps it cheap — a built data-lake offloads the heavy raw; compact rollups serve the live site.
Bring your providers; we bring the backbone. The group graph — 82,817 groups and 1.76M clinician affiliations — rolls a whole MSO or billing book into one view, every NPI scored against its real local peers, every memo white-labelable under your brand.
Honest by construction.
One backbone. Score your rates against the real market.
See one real finding free — your RateScore and one documented reimbursement opportunity, no PHI required. Unlock the full per-CPT, per-payer breakdown and your counteroffer on a short call.
Your structure depends on your NPIs, payer mix, and the opportunity in your own data, so we price it with you on a short call. Documented reimbursement opportunity is modeled, not guaranteed.
Every number here is the scope of the public estate we index toward — not a live row count. Coverage is disclosed on every result. Methodology & sourcing → · Our honesty standard →