LunaBill: Revenue, team and how it was built

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.

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.

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.

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.

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.

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.

Solo founder · sold 5 months after launch

It launched in the month that AI models became good enough to write a whole app. It sold to people who cannot program, it charged from day one, and it was sold to a company that already had millions of customers.

Solo founder · 37 months after launch, revenue growing

It launched the obvious application of a new model within weeks, with a pricing page on the first day. The founder built the parts around the model instead of a model, so every model upgrade improved the product for free. Then it moved from a consumer toy to business customers who stay.

Solo founder · 27 months after launch, revenue growing

Said US$245K a monthRecords US$263K MRRSaid less than the records

The founder took a twenty-year-old product category with no open-source entry and open-sourced all of it, which gave him millions of Docker downloads and 37,000 GitHub stars without a marketing budget. Revenue stayed small for a year. It multiplied when he turned the product toward people who automate their posting with n8n workflows and, from late 2025, with AI agents, which need an API-first scheduler and keep paying because they post without human effort.

Team of 2 to 10 · 19 months after launch, revenue falling

Said 500+ paying agenciesRecords 207 subscriptionsDid not hold

The founder had an audience before the product existed: a daily YouTube show about SEO since 2023 and an X account that has 62,000 followers today, so the first customers cost nothing. A developer co-founder built the software with AI coding tools. The product started as one plain rank tracker at US$19 a month, grew into a bundle at US$57 to US$2,997 a month, and by July 2025 the first payment of a new customer from a paid ad covered the cost of that ad.

Team of 2 to 10 · 3 months after launch

It is built for one kind of legal work, litigation, by a co-founder who practiced it. General AI chat tools have produced invented case citations that courts have punished, and Litmas AI sells a check of every citation against real court opinions as its main feature. The company stated that its demand came mainly from inbound marketing, and it priced per case so that small and contingency-fee firms can start small.

Solo founder · 7 months after launch

Designers often want a second opinion before a client review and have no colleague to ask. The maker is a product designer with more than 25 years of UX work, so the critique format follows how a senior designer reviews work: name what is unclear, then give three concrete changes. The first three critiques are free, and a subscription is needed after that.

Team of 2 to 10 · 7 months after launch

The founder, a lawyer who teaches negotiation, said that mediation works but is expensive and tied to office hours and calendars. Adri lets both sides answer at different times, and it makes the first proposal itself. The company then moved its focus from consumers to mediation providers that want a cheap first step for small disputes.

Solo founder · 37 months after launch

The founder is a practicing litigator who, in the company's words, built it inside his own firm because he needed it. Drafting litigation documents takes many hours of a lawyer's time, and the company's December 2023 entry says the tool does such work in about two minutes. Its pages answer the main fear of lawyers about AI, invented case citations, with citation links that open the source and a written credit guarantee.