FDA-cleared dental AI for pathology detection and patient education
Overjet builds FDA-cleared AI for dental diagnostics, with a tech stack split between legacy Windows/.NET desktop applications (C#, WPF, WinUI) and modern cloud services (React, Django, PostgreSQL, AWS/GCP/Azure). The hiring mix—14 engineers, 13 support, 9 sales—combined with active projects around Windows MAUI modernization, real-time communication, and sales automation reveals a company in transition: scaling revenue operations while refactoring its clinical desktop experience and rolling out NetSuite for backend accounting.
Notable leadership hires: Director of Engineering, Customer Success Director
Overjet is a Boston-based dental AI company founded in 2018 by MIT and Harvard experts. The company's core product uses machine learning to detect oral pathologies and help clinicians make diagnostic decisions with greater precision. The platform is FDA-cleared and positioned as an objective standard for oral health assessment. With 51–200 employees, Overjet serves dental organizations (practices, DSOs, labs) and is actively scaling sales, customer success, and finance functions across the US, India, UK, Egypt, Pakistan, and Bulgaria. Current operational focus includes reducing customer churn, improving net revenue retention, expanding accounts, and automating back-office workflows.
Overjet's stack spans legacy Windows/.NET (C#, WPF, WinUI, NET MAUI) for clinical applications and modern cloud services: React, Django, PostgreSQL, Node.js, Go, Python on AWS, GCP, and Azure. Desktop tooling includes WebSockets, WinAppDriver, and Azure DevOps.
Active projects include Windows MAUI application modernization, real-time WebSocket communication, sales force expansion and targeted campaigns, NetSuite adoption for accounting automation, equity/cap table reconciliation, and a security automation and vulnerability management program.
OVERJET's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.