$37M in funding empowers Tennr to bolster healthcare efficiency with document-reading ML models
Tennr, the company automating the messy, manual work holding healthcare organizations back, is announcing the completion of a Series B funding round—led by Lightspeed Ventures with participation from existing investors a16z and Foundation Capital—having raised $37 million. Bringing Tennr’s total capital raised to over $61 million, the latest funding will continue to support the company’s technological breakthroughs in document automation for the healthcare industry.
Tennr’s suite of document-reading machine learning (ML) models and its automation platform seek to alleviate the pains of healthcare’s messy documentation, lengthy clinical reviews, and inefficient back-and-forth information exchange. Acknowledging that, ultimately, quality medical care depends on a robust, efficient knowledge system, Tennr expedites millions of patients through the U.S. healthcare system with purpose-built solutions designed to process complex medical information.
“Our customers, spread across the U.S., run tight operations and process patients with excellent service. We align ourselves with these objectives that’s helping us drive growth,” said Trey Holterman, co-founder and CEO of Tennr. “In the face of fixed-fee structures on the revenue side and constant inflation on the cost side—they want to be known as the best place to send patients, but they have an insurmountable amount of admin work that they have to do to get the job done. So, whether they always know it or not, it actually really matters to them that we try to be the best in the world at reading checkboxes, and drive these models forward”
At the core of Tennr’s approach is turning paperwork into patient advantage by labeling, tagging, and categorizing each document passing through a medical practice. Having built out processes for automated intake, clinical audits and reviews, requests for more information, prior authorization requests, and eligibility and benefit checks, Tennr understands that, in healthcare, nearly every use case feels like an edge case. Meaning, the nuances of medical documentation are entirely composed of dynamic, complex subtleties that more generalized models cannot adequately accommodate.
For example, even in instances where a non-healthcare-specific challenge arises—such as reading checkboxes—the level of accuracy demanded by this specific field shadowed what popular large language models (LLMs) could deliver, according to Tennr.
“I think checkboxes are a good example of a situation where nothing on the market, paid or open source, was even close to hitting the accuracy requirements we needed,” said Holterman. “The forms you fill out at a clinic are mostly checkboxes and so we addressed that by building a checkbox reader. We applied novel vision techniques we’d learned about in 2022, with what had to be the world’s largest dataset of labeled checkboxes.”
Darius Reid, head of operations at Total Medical Supply, illustrated how Tennr was “completely transformative to our workflow. We’re now processing new patients in a fraction of the time it used to take, which has been a game-changer.”
“It's clear that Tennr's product is meeting a significant market need across the healthcare industry,” said Alex Kayyal, partner at Lightspeed. “Their workflow automation platform drives significant ROI for customers while improving the patient experience dramatically. We've been deeply impressed with the team's vision and execution and are excited to partner with Tennr as they bring more AI native capabilities to healthcare organizations.”
Tennr’s latest funding will enable the company to grow its research and engineering teams, as well as fuel its expansion into speciality practices. This will serve to bring Tennr closer to its vision, where healthcare practices will be able to communicate more like tech companies with tight, structured API responses, automated messaging, and clean data transfers, according to the company.
To learn more about Tennr, please visit https://www.tennr.com/.