Tennr automates patient referral processing and insurance authorization using proprietary vision-language models trained on payer criteria data. The tech stack—JavaScript, TypeScript, Python, React, plus Salesforce, Gong, Outreach, and Monday.com—reveals a dual-layer architecture: a consumer-facing automation engine paired with a sales and operations backbone. Hiring is broad across engineering, sales, and HR with mid-to-senior weight, while active projects span financial infrastructure, ML pipeline scaling, and revenue operations—indicating a company simultaneously shipping product, hardening internal systems, and scaling GTM.
Tennr is a healthcare operations automation platform founded in 2021 and based in New York. The company targets providers and health systems drowning in manual referral qualification, insurance pre-authorization, and denial management. Their core product uses machine learning to intelligently route patients and process payer rules, aiming to eliminate delays and prevent first-pass claim denials. The 201–500-person org is split between product engineering (scaling ML infrastructure and automation), a sales organization (using Salesforce, Gong, Outreach), and backend ops (Asana, Jira, NetSuite, QuickBooks for financial and payroll workflows). Active development covers high-volume workflow automation, performance optimization, and critical builds in financial and commission infrastructure.
Tennr's stack includes JavaScript, TypeScript, Python, and React on the front end; Salesforce, Gong, Outreach, and Monday.com for sales and operations; and Rippling, Greenhouse, and Ashy for HR and recruiting.
Tennr is headquartered in New York, NY and was founded in 2021 as a privately held company.
Tennr'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.