Tennr

Tennr uses AI to automate healthcare document workflows — referrals, prior authorizations, and fax intake — that still stall patient care across US medicine.

Overview

Tennr targets an unglamorous bottleneck: healthcare paperwork. Much of US medical coordination still runs on faxes, scanned forms, and manual data entry, and Tennr’s AI reads those documents, extracts the relevant information, and moves each case through the next step — scheduling, authorization, or routing — automatically. Its models are trained on medical documents specifically, handling messy scans and inconsistent formats that generic OCR struggles with. The platform integrates with practice management and EHR systems, and its analytics expose where referrals stall and how long each step takes. For specialty practices and health systems losing patients to process friction, Tennr turns document handling from a staffing problem into a pipeline. Tennr’s system flags incomplete or ambiguous documents for human review rather than guessing, keeping automation speed without introducing errors into clinical or billing workflows. Implementation focuses on mapping existing intake processes precisely, ensuring automation augments coordinator workflows instead of imposing a generic model that staff quietly abandon after launch.

Key Features

• Medical-document AI handling faxes, scans, and referrals
• Automated routing through scheduling, authorization, and intake steps
• Models tuned for messy real-world medical paperwork
• Integration with practice management and EHR systems
• Analytics exposing referral bottlenecks and cycle times
• Human-review flags for incomplete or ambiguous documents instead of guessing

Pricing

Tennr is sold through enterprise agreements with practices and health systems, priced around document volume and workflows covered. Implementation includes integration and process configuration with the operations team.

Who Is It For

Specialty practices, referral networks, and health systems whose patient volume is limited by document processing capacity rather than clinical demand or provider availability. It fits organizations that measure patient leakage in lost referrals and know that paperwork speed is a competitive, as well as clinical, issue.