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FONTEUM · FOR HEALTH-TECH

Audit-grade provider data with field-level provenance. Survives compliance review.

Most provider-data vendors say "we're accurate" and offer an NDA. We ship a per-dataset, per-field, versioned Audit Pack a buyer can attach to their internal audit response. Methodology is public. Reproducibility is documented. Limitations are explicit. PDF + JSON downloads are free.

See a sample Audit Pack →Schedule a 30-min discovery call →See pricing
AUDIT PACK · THE DIFFERENTIATOR

The compliance artifact your buyer's audit team needs

Every Fonteum dataset ships with a free, public, versioned Audit Pack: methodology version (vYYYY.MM.N), per-field provenance map, reproducibility statement, limitations stack, change history, compliance Q&A, and PDF + JSON downloads. Health-tech buyers attach it to their internal audit response. Procurement teams cite it during diligence. Compliance officers preserve it across renewals.

What changes for your buyer:the data conversation moves from "take our word for it" to "cite our methodology version in your audit." That changes who buys (data team → compliance owner), changes ACV (3-10× typical), and changes renewal dynamics (compliance budgets stick).

  • Fonteum Pilot: 1 Audit Pack per contracted dataset per quarter; 1 dataset/month AI-native export with daily refresh on the selected dataset.
  • Fonteum Standard: Monthly customer-scoped Audit Pack per dataset; all-datasets AI-native exports with weekly refresh.
  • Fonteum Enterprise: Per-delivery Audit Pack with methodology version pinned to the snapshot; all-datasets AI-native exports with custom narrative cadence and a dedicated cache tier.

Browse the 17 published Audit Packs → · Sample: Dermatology Audit Pack →

METHODOLOGY-AS-PRODUCT · THE BUYER-PASS-THROUGH SURFACE

The link your buyer's product points at

The Audit Pack above is the artifact a compliance officer attaches to an internal audit response. The methodology page is the public, durable URL their product points at — the citation in their footer, the link their auditor clicks, the reference their procurement team forwards. Every dataset ships one: /methodology/dermatology-supply, /methodology/cardiology-supply, /methodology/nursing-home-quality, and 14 more.

Each page renders the methodology version banner, last-refreshed timestamp from the §195 refresh-tracking layer, source provenance (registered family + Tier + cadence), reproducibility steps, limitations stack, full field schema with per-field source + confidence, version history with change rationale, four-format citation block (APA, Chicago, plain text, BibTeX), and a downloadable methodology PDF pinned to the active version. Indexable. Free. No login.

What changes for your buyer's buyer: the auditor stops asking your compliance officer to defend Fonteum. They click the link. Fonteum defends itself. The compliance review closes faster; the integration sticks longer.

Sample: Dermatology methodology page → · Global methodology + changelog →

EVIDENCE QUERY · PROVENANCE-GROUNDED Q&A

Generic NLQ returns a number. We return the evidence trail.

Natural-language questions about U.S. provider supply, answered with the source URL, last-checked timestamp, methodology version, and per-claim limitations the auditor needs to verify each claim independently. Try the public demo →

What changes for your buyer's buyer: the auditor stops asking where did this number come from. Every value in the answer carries a citation. Out-of-scope questions (predictions, payment data, vendor comparisons, single-provider PII fishing) refuse cleanly with the documented refusal code rather than hallucinating an answer.

How it's Ribbon-proof: the contract only works because the underlying data was built provenance-first (§192 per-field provenance, §194 Audit Pack, §195 refresh tracking, §196 versioned methodology pages). A vendor retrofitting LLM features on a non-provenanced data graph cannot ship this — the citations would have nothing to point at.

Public demo (free, 10/day per IP) → · Authenticated API contract →

AI-NATIVE EXPORTS · LLM-GROUNDED DATA WITH INLINE CITATIONS

The 4th differentiator. Designed for buyers building copilot, RAG, or patient-navigation LLM products.

Generic CSV/JSON exports are designed for ETL pipelines. AI-native exports are designed for LLM grounding: pre-chunked text representations with methodology embedded for grounding, citations embedded for defensibility, and source provenance per chunk so the buyer's LLM cites real Fonteum data — not hallucinated facts.

Three formats per dataset at GET /api/v1/exports/[dataset]/llm-ready:

  • NDJSON — newline-delimited, streaming-friendly. Pipe directly into an embedding worker without buffering.
  • JSON — single-document RAG envelope. Best for batch ingestion + indexing into a vector DB.
  • text-blocks — plain text, paste-into-LLM-prompt-ready, --- CHUNK --- delimiters.

Embedding-free is intentional. Buyers run their own embedding model (OpenAI / Voyage / Cohere / whichever fits their stack) and own their vector storage. We provide LLM-ready text + provenance + methodology metadata; they retain full control of their AI infrastructure. A 1-2 paragraph synthetic narrative is generated via Claude Sonnet on first request and cached per methodology version, so cache hits are free.

Why this is Ribbon-proof: retrofitting LLM-ready exports onto a non-provenanced data graph means inventing citations that don't trace anywhere. Our chunks cite real audit-pack methodology pages (example) backed by real public sources (CMS NPPES, U.S. Census PEP V2025). The buyer's compliance team sees citations in every LLM-generated response. Their auditor verifies via the public methodology page. The whole audit-grade trust stack works inside their LLM product.

Endpoint contract + integration examples (Pinecone / Chroma / PGVector) →

USE CASES

Provider-discovery data layer

When your patient-facing product needs a defensible, source-cited list of providers in a specialty + geography. NPPES Type-1 enumeration with state-level license matching where applicable.

Example: Dermatology results in Wyoming with last-checked dates and source URLs on every record.

Network-adequacy analysis

When a payer-network or care-coordination product needs to model provider-to-population ratios at state or county granularity. Per-100k density figures derived from the same per-source provenance contract.

Example: Per-state OBGYN supply at 2.52 / 100k, with the limitation footnotes a diligence team needs.

Access-gap visualizations

When you ship maps or dashboards that need defensible underlying counts. The downloadable CSV/JSON behind every research study is the same data we'd license — with source-row traceability for any state.

Example: Gastroenterology supply: 6 jurisdictions covering 14.7M residents below the AGA-aligned 4/100k threshold.

Sub-specialty enrichment

When your CRM or product database has provider names but lacks the NUCC taxonomy specificity to filter by sub-specialty. We provide the sub-specialty layer with explicit Type-1 / Type-2 disclosure where it matters.

Example: OBGYN sub-specialty breakouts (MFM, REI, GynOnc, Urogyn) with the §185 Type-1 NPPES disclosure pattern.

SAMPLE THE DATA — FREE

Every research study ships with a downloadable CSV

You can sample the data shape before scheduling a call. Each shipped study includes a downloadable per-state CSV with the same provenance shape we license to paying customers. Three concrete examples:

  • Dermatology supply by state (NPPES 2026) — active dermatologists, per-state per-100k figures, downloadable CSV/JSON
  • Cardiology supply by state (NPPES 2026) — active cardiologists, per-state per-100k figures, downloadable CSV/JSON
  • Gastroenterology supply by state (NPPES 2026) — active gastroenterologists, per-state per-100k figures, downloadable CSV/JSON
HOW A 90-DAY PILOT WORKS
  1. Discovery (30 min, free). We learn what specialties + geographies your product needs. You see the methodology, the limitations, and a sample CSV.
  2. Pilot scope (1 week). We agree on 1–3 specialty datasets, refresh cadence, and integration shape. Pricing range: $2,500 – $5,000 / month.
  3. Pilot agreement (signed, 1 week). 90-day term, 30-day no-penalty termination, mutual NDA, internal-use license. Net 30 invoice.
  4. Pilot delivery (Day 1 onward). CSV / JSON exports on the agreed cadence. Email support, business-hours response within 1 business day.
  5. Day-75 review. Joint check-in to assess fit. If pilot continues to Standard tier, the agreement converts. If not, the pilot ends cleanly at Day 90.

The pilot is designed so a procurement team can de-risk the buy. No long-term lock-in, no per-seat sprawl, no legal sprawl. Pilot agreement and security/SLA pages are linked from the discovery email.

PROCUREMENT TOOLKIT

Everything a procurement team typically asks for, already published:

  • Security posture — data scope, infrastructure, attestation roadmap (no overstatement)
  • SLA — uptime targets and support-response targets per tier
  • Refresh cadence — per-source data freshness, transparently stated
  • Methodology — how every published figure was computed
  • Data provenance — the per-record source/date/confidence contract
  • Standard B2B terms — pilot agreements supersede where they conflict

Ready to discuss a pilot?

30-minute discovery call. We learn your scope, you see the data. No commitment.

Email pilot@fonteum.com →Data platform overview →

FONTEUM · PILOT

Run a 90-day pilot. Public data only. No PHI.

Request access→ Read the methodology

Built on the authoritative federal record

The primary sources, named on every page.

These are the federal agencies whose public datasets Fonteum ingests and attributes — the issuing authorities, not customers or partners. Every figure on the site links back to one of them.

  • CMS
  • HHS-OIG
  • HRSA
  • FDA
  • NLM
  • NUCC
  • Census
  • BLS
  • BEA

See the full source registry, with license and refresh cadence for each →

Reproducible by design

Every figure traces to its federal source.

14-tuple provenance

Every rendered fact ties to a source URL, dataset ID, snapshot date, row key, and SHA-256 — the full chain-of-custody record.

Reproducible SQL

Each study ships the exact query behind its figures, run against the cited federal snapshot. Re-run it yourself.

Daily reconciliation

Published counts are reconciled against the upstream federal datasets on a daily cadence, with drift logged.

Named medical review

Reviewed by Jennifer Montecillo, MD, medical reviewer. Non-practicing medical reviewer.

Read the full provenance and attestation methodology →

Two doors

Use the free API and open data

Query providers, facilities, sanctions, and quality scores — each field carrying its federal source. Self-serve, no call to start.

Explore the API →Browse the data catalog →

Talk to us

Managed pilots, enterprise terms, and audit-ready, signed attestation packages for compliance, risk, and research teams.

Talk to us →
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Reviewed by Jennifer Montecillo, MD, medical reviewer. Non-practicing medical reviewer.

© 2026 Fonteum LLC. All rights reserved.

The U.S. healthcare graph AI can cite — every fact carries its source.

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The substrate, by the numbers

9.2Mgraph entitiesProviders, organizations, owners, and facilities
15.7Mlinked identifiersNPIs, CCNs, LEIs and more, resolved to entities
5Mgraph edgesSource-attested relationships between entities
44federal source familiesDistinct CMS, OIG, HRSA, FDA and peer datasets
35dataset pagesCitable, downloadable /data catalog pages
13reproducible studiesEach shipping the SQL behind its figures