Particle Health vs Tennr (2026)
Two answers to the question of how clinical information reaches an organization that does not already have it. Tennr reads what arrives, applying a proprietary vision language model to the faxes, forms and scanned referrals that still carry most inbound healthcare communication, and turning them into routed actionable referrals. Particle Health goes and gets what was never sent, querying the national interoperability networks through a single bidirectional interface with an enrichment layer on top. The distinction matters because organizations misdiagnose this constantly: a practice drowning in unprocessed faxes has an intake problem, while a practice whose patients received care elsewhere has a retrieval problem, and buying the wrong one leaves the actual gap untouched. Many organizations have both, in which case these are complementary rather than competing purchases.
- It is retrieval first, querying the national health information networks through a single bidirectional interface, so the data arrives from outside the organization rather than from the fax machine.
- The enrichment layer sits on top of genuine interoperability infrastructure, which is a harder asset to build than a document reader.
- For an organization whose gap is records held elsewhere rather than documents arriving unread, this is the product that closes it.
- Referral and document intake is the specific target and the vision language model reads unstructured inbound material directly, which is where the work actually is.
- The output is a routed actionable referral rather than extracted text, so the intake team gets a decision rather than a data set.
- For a practice losing referrals to intake friction, this addresses the revenue leak rather than the filing problem.
This comparison is published by AI Health Index, an independent research platform that compares healthcare AI vendors objectively. Particle Health and Tennr are each graded against the same capability taxonomy, from each vendor's own public materials and the regulatory record, under the AI Health Index verification standard. No vendor pays for placement, and no vendor has reviewed this page. How this evidence is graded
Plain facts
| Fact | Particle Health | Tennr |
|---|---|---|
| Primary category | Healthcare Administrative Automation | Healthcare Administrative Automation |
| Headquarters | New York, New York | New York, New York |
| Website | particlehealth.com | tennr.com |
Side by Side
Select any grade to read the note behind it.
Each vendor in one paragraph
Written to be quoted whole. Each paragraph opens the AI Health Index profile of the vendor: what the product is, who buys it and what it does.
Particle Health sells access to patients' medical records through a single API. It queries CommonWell, Carequality, eHealth Exchange and state HIEs, with ADT feeds and pharmacy fill data, returning FHIR R4, C-CDA or its own tabular format, and reports 320 million patients across more than 70,000 organizations, finding on average 90 percent of patients nationally.
Source: AI Health Index, August 2026
Tennr automates inbound document and referral operations for the organizations that receive them. RaeLM, the company's own vision language model, reads unstructured inbound material including faxes, scanned forms, portal submissions and handwritten orders, extracts the clinical and administrative data, and the platform evaluates it against payer criteria to establish what is covered, what documentation is missing and what should happen next.
Source: AI Health Index, August 2026
Questions buyers ask
How are Particle Health and Tennr priced and sold?
For Particle Health, the pricing unit is not stated.
With Tennr, no implementation fee, contract term or minimum appears. From the AI Health Index, drawn from each vendor's own published materials and the regulatory record, verified August 4, 2026. No vendor pays for placement.
How do Particle Health and Tennr handle patient data?
In Particle Health's case, the security page states that all protected health information is de-identified when used for internal analytics, and that data at rest is encrypted.
For Tennr, the privacy policy paraphrases the concept rather than naming the enumerated identifier method or an expert determination, and the two leave different residual risk. From the AI Health Index, drawn from each vendor's own published materials and the regulatory record, verified August 4, 2026. No vendor pays for placement.
Which settings and specialties do Particle Health and Tennr cover?
With Particle Health, the company also sells the same data to value based care organizations and payers for care gap closure and HEDIS, MIPS and Star Ratings reporting, with Signal alerts sold for readmission reduction.
In Tennr's case, the span reaches beyond where the evidence sits. Hospitals, health systems and specialty pharmacy each have a page and none has a named deployment, and the referral criteria work is inherently payer and service line specific, so nothing shows what is production proven outside equipment and specialty practice. From the AI Health Index, drawn from each vendor's own published materials and the regulatory record, verified August 4, 2026. No vendor pays for placement.
What evidence is published for Particle Health and Tennr?
For Particle Health, the home page quotes One Medical on gathering external health data before a first visit, xCures on growth and scalability, and Cureatr on pharmacist recommendations from discharge summaries, and the company reports 320 million patients, more than 70,000 organizations and 90 percent of patients found on average. No clinical evidence applies, since the product retrieves rather than decides.
With Tennr, the customer stories carry the detail. Home Medix reports referral processing dropping from 25 minutes to under 5, quadrupled intake volume and 32 days of staff time saved over six months. From the AI Health Index, drawn from each vendor's own published materials and the regulatory record, verified August 4, 2026. No vendor pays for placement.
Related comparisons
Other published head to head assessments involving these vendors or their closest peers.
These solve adjacent problems and a buyer should establish which one they have before comparing: unread inbound documents is an intake problem, while missing outside records is a retrieval problem, and the same organization frequently has both. Neither vendor publishes a touchless completion rate in comparable form, which is the measure that matters for intake, nor a match rate for retrieval. Neither publishes pricing.
For any product ingesting inbound clinical documents, establish retention and whether customer documents improve models, since the sender of a fax has consented to nothing and the patient in it even less.