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Clinic and practice admin

Front-office and back-office software for clinics, dental practices, pharmacies and drug makers: AI phone receptionists, patient recall, insurance checks, billing and claim follow-up, prior authorization and clinical-trial data. Consumer health apps are in Health and appearance.

Clinic and practice admin holds 11 of the 603 stories on Aiolum: 0 run by a solo founder and 11 by a team of 2 to 10. Together they report US$1M in verified outcomes; the largest is Aeva AI, $2M a year run rate (currency not stated), October 2026. 0 headline numbers carry evidence grade A (disclosed or verified), 0 grade B (independent press) and 1 grade C (founder claim), 5 are grade D (reported, not verified), and 5 have no revenue figure (grade E). The median story reached its headline number 11 months after launch. The founders are in 4 countries, most often United States and USA. The most common main channel is cold outreach (3 of 11). The tools named most often in their sources are Cloudflare (5), Calendly (4) and Google Analytics (3).

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Evidence gradesA disclosed or payment-verifiedB independent pressC the founder's own figuresD reported, not verifiedE no revenue figureHow we verify

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The revenue trend compares the latest months in the sources with the months before them. Falling means revenue is about 15% or more below the best recent months, or the sources report a fall. The headline number is the yearly figure or the sale value on each card.

11 of 603 stories shown

AI phone receptionist for allied-health clinics · New Zealand

Aeva AI

Evidence C
$2M/yr run rate

Team of 2 to 10 · 21 months after launch, revenue growing

The two founders first ran an AI calling agency for any industry, which barely covered costs and lost customers. In January 2025 they narrowed to one niche, allied-health clinics on one practice system, and built deep booking integrations and local-accent voices for it. The co-founder said that customers called the first price cheap, so they raised it.

Every number graded · 3 that failed before it
Prior authorization and benefit checks for prescribers · United States · Funded

Develop Health

Reported, not verified
$6M/yr reported

Team of 2 to 10 · 38 months after launch

In the United States many medicines need the insurer's approval before the pharmacy can fill them, and that approval still means forms, faxes and phone calls. The two founders had worked at healthcare software startups and built a system that reads the insurer's rules and the patient's chart and does the form work. The Lean AI Leaderboard listed it at US$6 million a year with 5 employees in March 2025.

Every number graded · 4 that failed before it
AI operations layer for the front office and billing of specialty medical practices · United States · Funded

Plena Health

Reported, not verified
$1M+ contracted ARR reported

Team of 2 to 10 · 8 months after launch, revenue growing

One founder's mother is a doctor, her clinic was the first user, and the founders say they spent years inside clinics before building. The founders say that, instead of one narrow tool, their engineers assemble reusable workflow blocks for each practice in days, so a practice can start with one painful task and add more. The founders said in June 2026 that 80% of growth came by word of mouth.

Every number graded · 4 that failed before it
AI receptionist and front office for dental practices · United States · Funded

Patientdesk.ai

Reported, not verified
$50K MRR reported

Team of 2 to 10 · 6 months after launch, revenue growing

The three founders ran a dental marketing agency and their own call center for two years before they built the product, so they knew where clinics lose patients: calls that go to voicemail after hours, and insurance questions that need a call back. They connected the voice agent to the clinic software that already holds the calendar, and added live insurance verification, which they say no other system did during the call.

Every number graded · 4 that failed before it
AI voice agents for insurance claim follow-up calls · USA · Funded

LunaBill

Reported, not verified
$428K live ARR

Team of 2 to 10 · 4 months after launch

The founders had worked inside healthcare billing before, so they knew that insurance follow-up calls are a large, repetitive and expensive part of the work. A voice model can now hold this kind of short, scripted business conversation. The company sells to health systems and billing firms through pilots, and the founders said in November 2025 that every pilot had become a paying customer.

Every number graded · 3 that failed before it
AI electronic data capture software for clinical trials · USA · Funded

Harbor

Reported, not verified
$15.6K/mo, founder-reported

Team of 2 to 10 · 11 months after launch

The founders say that setting up this kind of database by hand takes companies two to three months per trial, and that clinic staff spend hours typing records into it. Harbor turns the protocol into a draft database in about 10 minutes and the paper records into form entries with a confidence score for each value, so a small sponsor can start a study in days.

Every number graded · 4 that failed before it
AI recall calls and texts for dental practices · USA · Funded

10x

No revenue figure
Dozens of practices live

Team of 2 to 10 · 0 months after launch

Dental practices already hold the names of patients who are overdue for a cleaning or who never scheduled the treatment a dentist proposed. The front desk is busy with the patients in the room and rarely calls that list. 10x sells a machine that calls the list every day and only counts a booked appointment as done.

Every number graded · 3 that failed before it
AI treatment coordinator that brings dental patients back to unscheduled treatment · United States · Funded

Healink

No revenue figure
Six paying practices

Team of 2 to 10 · 12 months after launch

Many patients leave the dental chair with a printout of procedure codes and never book the treatment that was recommended. The home page says 50 to 70% of recommended treatment is never completed. The front desk then spends hours calling and texting the same patients. Healink was started by a software engineer and her brother, a dentist, to automate that follow-up.

Every number graded · 3 that failed before it
AI agents for dental billing: insurance verification, claims, payment posting and AR follow-up · United States · Funded

Lavender Health

No revenue figure
30+ dental practices

Team of 2 to 10 · 8 months after launch, revenue growing

Dental offices spend staff hours on phone calls, insurer portals and fax machines to get paid for work already done. The company's site says that most dental software stores this work and Lavender does it. Its archived site shows that it started in early 2026 with an AI-assisted offer for medical practices and by May 2026 had moved to dental practices only.

Every number graded · 2 that failed before it
AI documentation and billing suggestions for German dental practices · Germany · Funded

Dentero

No revenue figure
200+ practices claimed

Team of 2 to 10 · 20 months after launch, revenue growing

German dental billing has three fee schedules and a rule that a fee above 2.3 times its base value needs a written reason, so a practice that documents a treatment badly loses fees, the company says, and cannot answer later questions about a bill. Dentero was built by a CEO who, the site says, grew up with dental billing and has seen more than 1,000 practices from the inside, with a long-time billing expert as advisor. It sits on top of the practice software that practices already have, instead of replacing it.

Every number graded · 3 that failed before it
AI phone system and front-desk agent for dental practices · USA · Funded

Newton

No revenue figure
Hundreds of practices

Started small, grew after funding · 33 months after launch

A dental front desk handles phone calls, patients at the counter, insurance checks and reminders at the same time, often with five or six separate tools. Missed calls and unfilled cancellations are lost appointments. Newton replaces the office phone system itself, so that every call, by staff or by the AI, runs through one platform and is written to the patient record.

Every number graded · 3 that failed before it
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The next verified one-person AI business goes here. Same structure, same evidence grades.

Every number on these cards carries an evidence grade. How Aiolum verifies explains the evidence grades and the five parts of each story.