Patient-facing clinical AI, built by physicians

Doctronic is redefining patient care with the leading clinical intelligence platform, combining medical AI chat and licensed physicians, in your system.

From medical consult to triage and care gap closures, Doctronic extends clinical capacity, reduces surgery cancellations and gets people to the right specialists while cutting avoidable ED and urgent care spend.

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30 million

AI-patient interactions¹

70+

Patient Net Promoter Score²

< 5 min

Average wait to see a physician³

Outcomes

What changes when care starts with Doctronic

One clinical AI chat can automate routine work, keep care in network, reduce avoidable ED visits, and open a path to closing care gaps. Here’s what we see on Doctronic today, and what we’d measure together in your population.

An older man with a cane and his daughter arriving at a hospital clinic reception
For health systems

Expand access, extend clinical capacity

Increase clinical capacity, reduce burnout

5x

more surgical patients reached by the same PAT team, projected with Doctronic doing the pre-op intake.⁴

Patients reach the right specialist sooner

10%

of chats surface a specialist need⁵

Routine needs, resolved before they reach your team

68%

of chats resolved in the AI consultation, no escalation⁶

A woman at her kitchen table on a sunny morning, smiling as she reads a reply on her phone
For health plans

Close care gaps and lower total cost of care

When a chat sounds like an ER visit

86%

of chats headed to the ED, based on the user’s own description, were resolved on Doctronic or directed to office care⁷

Each chat costs a fraction of what it saves

$60–$103

projected savings per chat⁸

Physician visits only when members truly need one

6.3%

of users who had a medical AI consult opted to see a human provider at Doctronic⁹

Read the evidence

Put Doctronic to work in your system

Here’s where health systems and health plans begin.

For health systems

Pre-admission testing (PAT)

Complete intake and history before the pre-admission visit, so surgical patients arrive ready for their procedure.

Virtual ED triage

Triage symptoms after hours and send each patient to the right site of care, so your ED sees the patients who need it.

Specialty referrals

Gather the history and workup up front, then book patients directly with your specialists.

For health plans

Care navigation

Guide members to the right level of care 24/7, cutting avoidable ED visits and inbound calls to member services.

Risk stratification

Build each member’s clinical picture with every conversation, surfacing rising risk while there’s still time to act.

Care gap closure

Find open gaps like lapsed refills and overdue screenings, then help members close them in network, supporting HEDIS and Stars performance.

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Clinical
Intelligence

Behind every step of the patient journey

Knows the medicine

Physician-written clinical guidelines and real-time safety monitoring

Knows the patient

Medical and Rx history with ongoing clinical memory

Knows your system

Your specialists, network, and care pathways

How it works

Blood in the urine Tuesday at 8:05 AM, at urology next Thursday

A 64-year-old former smoker messages your portal before work. Doctronic rules out an emergency, recognizes a high-risk finding, and books him straight into your urology clinic with the workup outlined.

01 Engage · 8:05 AM

A single front door

Patient messages your system’s portal:

Blood in his urinePainless, no feverPCP once a year, no urologist yet
I noticed blood in my urine this morning. No pain, no fever.

Thanks for telling me. Even if it clears up, this needs a check. A few quick questions first.

Ask a question about your health…

02 Synthesize · 8:09 AM

The AI sees the whole picture

  • Pulls chart, Rx, and outside records
  • Notes daily aspirin and smoking history
  • Screens for clots, retention, heavy bleeding, fever, and flank pain
  • Checks for look-alikes, like beets or certain medicines
  • Flags a high-risk finding that needs urology

Nov 3 · 8:09 AM

Doctronic Report

Assessment & PlanVisible blood in urine in a former smoker: a high-risk finding, even on aspirin.

Emergency screen: no red flags. Urology referral recommended, with the standard workup.

SOAP Note (for Physicians)Sent to your EHR with the plan
03 Deliver + Route · Next Thursday

Straight to the right specialist

  • SOAP note added to the EHR with the standard workup outlined
  • Patient booked directly with urology in your network
  • High-risk symptom reaches the specialist quickly
Urology visit, in network Next Thursday · 10:30 AM Urology · [Clinic name] Upcoming
RescheduleCancel
Files View SOAP note

Illustrative example of a deployment workflow.

Clinical safety

Clinical safety built into every interaction

Multi-functional safety layer

Your cases, guidelines & benchmark

Simulated-patient testing

Doctronic Forge creates custom benchmarks based on your population and caseload, then tests and scores the clinical AI on simulated patients before it meets a real one.

Case under test: facial pain

Red flag: numbnessCaught
HistoryComplete
Diagnosis + planCorrect
Safety reviewNo harm
Safety in real time

Real-time safety checks

Doctronic Guardians run alongside every conversation, screening each message in real time for emergencies and clinical risk. Depending on severity, they warn, escalate to a physician, or block the response.

Warn
Escalate
Block
Accuracy

Multi-agent decision engines

Specialized agents evaluate each case, grounded in clinician-written guidelines and informed by patient context

  • Agent 1
  • Agent 2
  • Agent 3
→ Decision
Interpretability

Step-by-step reasoning

See why the AI asked each question and made each recommendation, step by step, with every decision logged for audit.

Reasoning trace

01
Red flags screenedClear
02
Guideline appliedHeart failure
03
Decision loggedNext-day HF clinic visit

Built by clinicians, for patients

With board-certified physicians licensed in all 50 states and DC

Portrait of Adam Oskowitz, MD

Adam Oskowitz, MD, PhD

Co-founder and CEO

Portrait of Sarah Gilson

Sarah Gilson, MD, MS

Director of Autonomous Systems

Portrait of Bennett Waxse

Bennett Waxse, MD, PhD

MTS, Clinical

Validated

Independently reviewed by the State of Utah

In Utah’s published review of our AI prescription renewals¹⁰

100%physician reviewed
97%of AI-approved prescription refills were confirmed by at least one physician on a review panel
0safety concerns

See Doctronic in your system

Bring a problem, such as access, pre-admission testing, avoidable ED use, or care gaps. We’ll show you how Doctronic would work in your system, and the outcomes we’d measure together.

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Sources

  1. 1. 30 million AI-patient interactions. Source: Doctronic Clinic 2026
  2. 2. Patient Net Promoter Score of 70+. Source: Doctronic Clinic 2026
  3. 3. Average wait to see a physician under 5 minutes. Source: Doctronic Clinic 2026
  4. 4. Modeled. Pre-admission testing (PAT) case study. Today, a PAT team of 15 FTEs covers 20% of a system’s 350,000 surgeries a year; covering every surgery would take 75 FTEs. With Doctronic handling pre-op intake, the projection is that the same 15 FTEs cover 100% of surgeries, 5x the patients reached.
  5. 5. Doctronic cost-offset model input: in 10,000 de-identified Doctronic chats, the AI recommended specialist care in 10.2%.
  6. 6. Modeled. Doctronic ROI model, April 2026, using transition probabilities from 10,000 Doctronic chats.
  7. 7. Doctronic Research Insights, Reducing ER Visits (October 2026). Of 8,456 chats in the analysis sample, 429 (5%) carried emergency-level intent: the AI scored the user’s own description as emergency-level (counterfactual urgency 7 to 8) and judged the chat would otherwise have ended in the ED. A physician encounter’s disposition supersedes the AI recommendation. These figures describe where each chat ended and where the user was directed. They are platform dispositions, not verified records of where users actually went afterward.
  8. 8. Modeled. Doctronic cost-offset model; manuscript under peer review at The American Journal of Managed Care. Decision-analytic projection for a hypothetical commercial employer population, 2026 US dollars; counterfactual care seeking inferred from users’ messages, not yet validated against claims. The $4.10 program cost per chat is the model’s annual program cost for a 200,000-life system at 15% uptake (about $123,000) divided by the 30,000 chats it generates (Health System Savings, October 2026).
  9. 9. 6.3% of users opted to see a human provider. Source: Doctronic Clinic 2026
  10. 10. Utah Department of Commerce, Office of AI Policy, Doctronic Outcomes (May 2026).