LunaBill

LunaBill is building AI Voice callers for healthcare billing teams. Insurance claim follow-up calls account for the 80% of the daily workload of a healthcare billing team, with each call averaging 30 minutes.

Since our launch in July we are now at $764K in contracted ARR, of which $428K is live revenue and the rest will go live by January 2026. Our customers see a 10x increase in claims followed up per biller in the first week and we have converted 100% of pilots to paying customers. We have automated 50,000+ calls and signed partnerships with top healthcare leaders like UC health systems, Mayo, Experian Health and more.

The founders have known each other for over a year. Suhail is a 2x founder, with 3+ years of experience building in healthcare including operating a medical billing company with 200+ healthcare clients. David founded Skiesoft, Taiwan’s biggest healthcare AI scribe company, used by 120k+ healthcare professionals. He also worked as a data scientist at UCSF, building models to audit medical-coding accuracy. Yash was a researcher at various hospital systems including Mayo Clinic.

High-Level Overview

LunaBill is an AI-driven platform that automates insurance-related phone calls for healthcare billing teams, significantly streamlining the medical billing process. Its AI voice agent, Luna, handles tasks such as claim status inquiries, accounts receivable (A/R) recovery, and appeals follow-up, enabling billing teams to reclaim thousands of hours weekly and focus on higher-value work. The platform is HIPAA-compliant, ensuring patient data privacy, and has demonstrated strong growth by automating over 150,000 insurance calls monthly and recovering more than $32 million in revenue for its clients[1][2][4].

Founded in 2024, LunaBill serves healthcare providers and billing companies by addressing the costly and time-consuming challenge of insurance phone calls, which traditionally average 25 minutes each and contribute to billions in delayed or denied payments annually. By automating these calls end-to-end with AI trained on over 1.2 million real call transcripts, LunaBill boosts billing team productivity by approximately 12x, enabling up to 300 claim follow-ups per day compared to 25 previously[2][4].

Origin Story

LunaBill was founded in 2024 by Yash Raj Singh Thakur, David Day, and Suhail Parry, who met at the Berkeley AI Hackathon where they initially built an AI nurse. Motivated by their shared experience with the operational pain points in healthcare billing, particularly the inefficiency of insurance phone calls, they developed LunaBill to tackle this challenge. Early traction included partnerships with top healthcare systems and three major enterprise billing companies, validating the product’s impact and market fit[1][2].

Core Differentiators

• AI Voice Agent Fine-Tuned on Extensive Data: LunaBill’s AI is trained on over 1.2 million real insurance call transcripts, enabling it to understand complex payer logic and sound natural in conversations[2].
• End-to-End Automation: The platform automates the entire insurance call process, including claim status checks, appeals, and reprocessing, reducing manual workload drastically[1][2].
• HIPAA Compliance: Ensures patient data privacy and security, a critical requirement in healthcare billing[1].
• Rapid Setup and Integration: Users can quickly set up accounts, upload claims via Excel or CSV exports from EHR or practice management software, and monitor call progress in real time through a dashboard[4].
• Proven Productivity Gains: Enables billing teams to complete 12 times more claim follow-ups daily, reclaiming over 20,000 staff hours weekly and recovering millions in lost revenue[2][4].
• Strong Partnerships: Collaborations with leading healthcare systems and billing companies enhance credibility and market reach[2].

Role in the Broader Tech Landscape

LunaBill rides the wave of AI automation and digital transformation in healthcare, addressing a critical bottleneck in medical billing—manual insurance calls that delay payments and increase operational costs. The timing is favorable due to rising healthcare costs, increasing complexity in payer systems, and growing demand for efficiency and compliance in billing operations. By automating these interactions, LunaBill helps unlock billions in delayed payments, reduces administrative burden, and accelerates revenue cycles, influencing the broader healthcare IT ecosystem toward more AI-driven operational solutions[2][4].

Quick Take & Future Outlook

Looking ahead, LunaBill is poised to expand its market penetration by deepening integrations with electronic health records (EHR) and billing platforms, scaling its AI capabilities, and broadening its client base across healthcare providers and billing companies. Trends such as increasing adoption of AI in healthcare operations, regulatory emphasis on data security, and the ongoing need to optimize revenue cycle management will shape LunaBill’s growth trajectory. Its influence is likely to grow as it sets a new standard for automation in healthcare billing, potentially expanding into related administrative tasks and payer-provider communications.

In summary, LunaBill exemplifies how AI can transform a traditionally manual, costly process into a scalable, efficient operation, unlocking significant value for healthcare providers and the broader medical billing ecosystem[1][2][4].