Tennr Company Profile

Background

Overview

Tennr is a New York-based healthcare technology company founded in 2021 by Trey Holterman, Tyler Johnson, and Diego Baugh. The company specializes in automating healthcare operations, particularly focusing on streamlining the processing of medical documents such as faxes, which remain prevalent in the industry. By leveraging artificial intelligence (AI), Tennr aims to enhance efficiency, reduce errors, and improve patient care coordination within healthcare organizations.

Mission and Vision

Tennr's mission is to revolutionize healthcare administration by automating and streamlining the handling of medical documents, thereby addressing inefficiencies in the U.S. healthcare system that rely on legacy technologies like fax machines. The company's vision is to create a seamless, efficient, and error-free healthcare environment through the integration of advanced AI solutions.

Primary Area of Focus

Tennr focuses on automating back-office tasks in healthcare, with a particular emphasis on processing medical documents such as faxes. The company's AI-powered platform integrates with existing healthcare workflows, including fax providers, on-premise file storage systems, and electronic health records (EHRs), to extract key information and automate associated tasks like referral processing, payment posting, claims auditing, and medical record management.

Industry Significance

In an industry where fax machines are still widely used, Tennr's innovative approach addresses a critical gap by automating the processing of medical documents, thereby reducing manual errors, improving operational efficiency, and enhancing patient care coordination. This positions Tennr as a significant player in the healthcare technology sector, contributing to the modernization and digital transformation of healthcare operations.

Key Strategic Focus

Core Objectives

• Automation of Healthcare Operations: Tennr aims to automate complex and repetitive tasks within healthcare organizations, such as reading medical records and identifying billing errors, to improve efficiency and reduce costs.

• Enhancement of Patient Care Coordination: By streamlining processes like patient referrals and medical record management, Tennr seeks to improve the coordination of care, ensuring patients receive timely and appropriate treatments.

Specific Areas of Specialization

• Medical Document Processing: Tennr specializes in automating the processing of medical documents, particularly faxes, to extract relevant information and integrate it into healthcare workflows.

• Referral Management: The company focuses on automating the referral process between primary care providers and specialists, reducing delays and improving patient outcomes.

Key Technologies Utilized

• Artificial Intelligence (AI): Tennr employs AI models, including its proprietary RaeLM™ 7B, trained on over 3 million documents, to read and process medical paperwork, significantly reducing billing errors and enhancing patient referrals.

• Machine Learning Algorithms: The company utilizes machine learning algorithms to interpret complex medical documents, including handwritten notes, and integrate the extracted data into healthcare systems.

Primary Markets or Conditions Targeted

Tennr primarily targets healthcare organizations, including hospitals, clinics, and specialty practices, aiming to automate back-office operations and improve patient care coordination. The company's solutions are designed to address inefficiencies in the processing of medical documents, particularly faxes, which are still widely used in the healthcare industry.

Financials and Funding

Funding History

• Series C Funding (June 2025): Tennr raised $101 million in a Series C funding round led by IVP, with participation from existing investors including Andreessen Horowitz and Lightspeed Venture Partners. This round valued the company at $605 million.

• Series B Funding (October 2024): The company secured $37 million in a Series B funding round led by Lightspeed Venture Partners, with participation from existing investors Andreessen Horowitz and Foundation Capital.

• Series A Funding (March 2024): Tennr raised $18 million in a Series A funding round led by Andreessen Horowitz, bringing its total funding to over $25 million at that time.

Total Funds Raised

As of June 2025, Tennr has raised a total of $159.81 million across multiple funding rounds.

Notable Investors

• Andreessen Horowitz (a16z): A prominent venture capital firm that has participated in Tennr's funding rounds, including the Series A and Series C.

• Lightspeed Venture Partners: Another leading venture capital firm involved in Tennr's funding, notably leading the Series B round.

• IVP: A venture capital firm that led Tennr's Series C funding round in June 2025.

Intended Utilization of Capital

The funds raised are intended to expand Tennr's research and sales teams, scale operations, and further develop its AI-powered platform to meet the growing demand for its services in automating healthcare operations.

Pipeline Development

Key Pipeline Candidates

Tennr's primary focus is on developing and enhancing its AI-powered platform for automating the processing of medical documents, particularly faxes, to improve healthcare operations and patient care coordination.

Stages of Clinical Trials or Product Development

As a technology company, Tennr does not engage in clinical trials. Instead, it focuses on the continuous development and refinement of its AI models and platform to address the evolving needs of healthcare organizations.

Target Conditions

Tennr's solutions are designed to address inefficiencies in the processing of medical documents, including faxes, which are still widely used in the healthcare industry.

Relevant Timelines for Anticipated Milestones

Tennr has not publicly disclosed specific timelines for upcoming product milestones.

Technological Platform and Innovation

Proprietary Technologies

• RaeLM™ 7B: Tennr's proprietary AI model trained on over 3 million documents to read and process medical paperwork, significantly reducing billing errors and enhancing patient referrals.

Significant Scientific Methods

• Machine Learning Algorithms: Tennr employs machine learning algorithms to interpret complex medical documents, including handwritten notes, and integrate the extracted data into healthcare systems.

Leadership Team

Executive Profiles

• Trey Holterman: Co-Founder and Chief Executive Officer. Trey is a former All-American rower and computer science major who worked as a software engineer at Strava before co-founding Tennr.

• Tyler Johnson: Co-Founder and Chief Technology Officer. Tyler studied computer science at Stanford University and worked in technical consulting before co-founding Tennr.

• Diego Baugh: Co-Founder and Chief Product Officer. Diego studied computer science at Stanford University and previously worked at Goldman Sachs before co-founding Tennr.

Competitor Profile

Market Insights and Dynamics

The healthcare technology sector, particularly in the realm of AI-driven solutions for healthcare operations, is experiencing rapid growth. Companies like Tennr are addressing critical inefficiencies in healthcare administration, presenting significant opportunities for innovation and market expansion.

Competitor Analysis

Tennr's competitors include companies such as Orbita, Impilo, and Kyruus Health, which also focus on healthcare technology solutions.

Strategic Collaborations and Partnerships

Tennr has engaged in various partnerships to enhance its market position and innovation capacity, including collaborations with ICONIQ to improve healthcare referrals and with Monolith for marketing initiatives.

Operational Insights

Tennr's focus on automating the processing of medical documents, particularly faxes, addresses a significant inefficiency in healthcare operations, providing a distinct competitive advantage in the market.

Strategic Opportunities and Future Directions

Tennr is well-positioned to expand its product offerings, including developing a network feature for primary care physicians and patients to track referrals and payments, and tools for verifying insurance information.