Mandolin vs Tennr (2026)
Mandolin and Tennr automate document and insurance work for organizations receiving referrals. Mandolin focuses on starting and sustaining specialty drug treatment. Tennr handles inbound referral operations across a wider mix of providers, including equipment suppliers, infusion services and physician groups. Mandolin reads charts and referrals, investigates benefits, estimates patient costs and follows authorization and claims activity through existing interfaces, fax and telephone. Agents can enter records and submit requests, while treatment necessity and safety decisions stay with clinicians. Conflicting fields and ambiguous records require review, and call transcripts preserve an audit trail. Anonymous customer accounts describe faster intake and fewer backlogs without dated evaluation methods. Tennr's RaeLM reads faxes, scans and other inbound material, extracts data and checks payer criteria. Outreach agents pursue missing information, while Tennr Network shares referral status across participants. Autopilot completes work described as high confidence, without stated thresholds or a review sampling rate. Named customer stories report shorter handling times and greater throughput without independent evaluation or a published share of fully automatic work. Mandolin fits infusion and specialty pharmacy teams connecting intake to benefits, authorization and continuing claim follow up. Tennr fits organizations coordinating a broad inbound referral queue and the parties supplying missing information. Mandolin follows specialty therapy administration through treatment access, while Tennr turns incoming documents into tracked referral actions.
- Specialty drug access is the main administrative workflow.
- Benefits investigation and patient cost estimates need to follow intake.
- Agents need to work through existing screens, fax and telephone.
- Infusion or pharmacy teams need ongoing claim follow up.
- Inbound referrals span several provider or equipment workflows.
- Referring and receiving organizations need shared referral status.
- Staff need outreach for missing documents and information.
- Document intake needs to connect with a configurable automatic processing layer.
This comparison is published by AI Health Index, an independent research platform that compares healthcare AI vendors objectively. Mandolin 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 | Mandolin | Tennr |
|---|---|---|
| Primary category | RCM & Prior Auth AI | Healthcare Administrative Automation |
| Headquarters | San Francisco, California, United States | New York, New York |
| Website | mandolin.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.
Mandolin automates the administrative work required to start and sustain specialty drug treatment. Its agents read referrals and clinical records, investigate insurance benefits, estimate patient costs, assemble prior authorization submissions and follow claims through payer portals and calls.
Source: AI Health Index, October 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, October 2026
Questions buyers ask
How are Mandolin and Tennr priced and sold?
For Mandolin, the current offer spans intake, benefits investigation, patient cost estimation, prior authorization and claim follow up, but there are no public subscription figures, transaction rates or package boundaries. It is unclear whether charges depend on locations, patients, workflows, completed tasks or another unit.
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 October 15, 2026. No vendor pays for placement.
How do Mandolin and Tennr handle patient data?
In Mandolin's case, the policy permits deidentified or aggregated information to train, validate and improve models, and requires appropriate safeguards or explicit BAA permission for outside model development. Retention follows customer instructions, contractual requirements and the purpose of processing, followed by deletion or anonymization when information is no longer needed.
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 October 15, 2026. No vendor pays for placement.
What evidence is published for Mandolin and Tennr?
With Mandolin, the available accounts do not connect a named customer to a dated, reproducible performance study or independently measured patient outcome.
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 October 15, 2026. No vendor pays for placement.
Related comparisons
Other published head to head assessments involving these vendors or their closest peers.
Mandolin is the trading name of Coral Automation in San Francisco; Tennr is based in New York. Neither publishes current fees or charging units. Both describe using deidentified data for model improvement, with the applicable terms set in their service and privacy materials.