Notable vs Tennr (2026)
Both automate the administrative front door and enter it at different points. Notable runs agents across the whole access and revenue path, from intake, registration and scheduling to referrals, prior authorization, denials and care gap outreach, which suits an organization where several teams are underwater. Tennr works the inbound document itself. RaeLM, its own vision language model, reads faxes, scans, portal submissions and handwritten orders and checks them against payer criteria, and Tennr chases the missing information, with a network that shows referring and receiving providers where a referral stands. If referrals and orders arriving on paper are where you lose revenue, Tennr is pointed at that. If the problem spans access, billing and care operations, Notable is the broader platform.
- Workflow coverage across access, revenue cycle and care operations, with a no code builder and a connector hub into Epic, Oracle Health, MEDITECH, athenahealth and payer portals.
- Published automation figures, such as 97 percent of in scope referrals automated and 15 percent of copays collected with no touch.
- A trust center listing HITRUST, SOC 2 Type 2, PCI DSS and ISO/IEC 27001.
- Its own vision language model for unstructured inbound material, reported as trained on more than 100 million anonymized healthcare documents and 8,000 sets of payer criteria.
- Payer criteria checks, triage, and outreach that chases missing information from providers, payers and patients, with an Autopilot layer for high confidence work.
- Tennr Network, a shared view of referral status for referring providers, receiving providers and patients, with around 320,000 partners.
This comparison is published by AI Health Index, an independent research platform that compares healthcare AI vendors objectively. Notable 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 | Notable | Tennr |
|---|---|---|
| Primary category | Health System AI Platforms | Healthcare Administrative Automation |
| Founded | 2017 | Not recorded |
| Headquarters | San Mateo, California | New York, New York |
| Website | notablehealth.com | tennr.com |
Side by Side
Select any grade to read the note behind it.
Product updates
The latest logged changes from each vendor, newest first, each linked to its source.
Notable
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Product / capability
Notable launched Flow Compass, an AI assistant inside Flow Studio that answers operators' questions about their automated workflows, runs and costs, drawing on the health system's own flows, connected EHR and clearinghouse data, and calls and faxes on the platform.
Source
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.
AI agent platform for health system and health plan operations. Agents work patient access (intake and registration, scheduling, referrals, order transcription, pre-procedure instructions by voice), revenue cycle (patient estimates and copay collection, prior authorization, appeal letters, denials), care operations (care gap outreach, chart review, risk adjustment) and the contact center, including a voice assistant answering patient calls around the clock.
Source: AI Health Index, September 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, September 2026
Questions buyers ask
How are Notable and Tennr priced and sold?
For Notable, the platform is sold to health systems and health plans through a demo, packaged as AI agents across patient access, revenue cycle, care operations and the contact center, with Flow Builder, Sidekick and a Connector Hub for integrations, and a Builders Program for partners. The trust center lists a master services agreement among its documents.
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 September 25, 2026. No vendor pays for placement.
How do Notable and Tennr handle patient data?
In Notable's case, all access to information within the platform is logged immutably, traceable to individual users, and reviewed regularly. Beyond that the platform page says data security follows industry best practice with details on request and that privacy of customer data is 'top of mind'.
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 September 25, 2026. No vendor pays for placement.
What evidence is published for Notable and Tennr?
With Notable, the figures are vendor-published without independent evaluation, and the revenue figures measure documentation captured rather than conditions confirmed on audit.
In Tennr's case, 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 September 25, 2026. No vendor pays for placement.
Related comparisons
Other published head to head assessments involving these vendors or their closest peers.
Both records were reviewed on this site in September 2026. Tennr's privacy policy says it uses deidentified data for research and development and to refine its models, and the sender of a fax has agreed to none of that; ask what leaves your organization.
Ask both for completion rates on documents that look like yours, since a demonstration on a clean electronic referral proves little about the fax queue. Ask too how they check that agents deciding which referrals move perform evenly across patient groups.