Dental practice software for analytics, patient communication and payments
Practice by Numbers sells an all-in-one operations platform to dental practices and groups, integrating with Dentrix, Dentrix Ascend and Open Dental. Its stack carries a serious telephony layer (Kamailio, OpenSIPS, FreeSWITCH, Asterisk, WebRTC) alongside Python/Django and Go, and job posts center on VoIP reliability and an AI receptionist, pointing to a push into voice-driven front-desk automation. Hiring is accelerating, engineering-heavy and senior-skewed.
Practice by Numbers is a privately held software company founded in 2015 and headquartered in Redmond, WA, with 51–200 employees. It serves dental practices, dental groups and larger dental organizations with a single platform covering practice analytics, patient communication, reputation management, online scheduling, online payments, patient forms and insurance verification. The company was founded by dentists. It integrates with dental practice management systems including Dentrix, Dentrix Ascend and Open Dental, and runs its product on AWS and GCP. Hiring spans the United States and India.
Python, Django, PostgreSQL, SQLAlchemy, Redis, Go, Docker and Kubernetes on AWS and GCP, plus a telephony stack of Kamailio, OpenSIPS, FreeSWITCH, Asterisk and WebRTC. HubSpot and Gong support sales.
Job posts point to an AI receptionist, mobile and front-desk kiosk apps, scaling telephony and VoIP reliability, and building out an SDR engine and sales organization.
Hiring is accelerating in the United States and India, weighted toward senior engineering roles, with additional openings in marketing, sales, support, design and product.
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Practice by Numbers'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.