Tennr

Company Overview

Tennr is a healthcare technology company that specializes in optimizing back-office operations for healthcare practices of all sizes. Founded by a team with backgrounds in computer science, machine learning, and healthcare, Tennr aims to streamline administrative processes in healthcare settings using advanced artificial intelligence and automation technologies.

The company’s core offering is a document reasoning model called RaeLLM™ 7B, which has been trained on over 3 million healthcare documents. This AI-powered system is designed to read, reason, and respond to healthcare paperwork with a reported 97% human auto-approval rate, significantly reducing the manual workload for healthcare administrative staff.

Products Overview

Tennr’s primary product is its AI-powered automation system for healthcare administrative tasks. The system’s key features and capabilities include:

1. Document Classification: Automatically categorizes incoming documents such as orders, patient information, and billing-related papers.

2. Information Extraction: Extracts and cleans up patient information, diagnosis details, and qualification criteria from documents.

3. Patient Qualification: Assesses patient eligibility for services, even when dealing with poor handwriting quality.

4. Automated Information Requests: Automatically requests missing information via fax or automated calls.

5. Insurance Eligibility Checks: Verifies if the practice accepts specific insurance plans, considering nuanced payor guidelines.

6. Prior Authorization: Seeks prior authorization for treatments, including form submission and portal interactions.

7. Patient Chart Creation: Automatically creates patient charts and integrates relevant information into existing systems.

8. EHR Integration: Seamlessly integrates with various Electronic Health Record (EHR) systems.

9. Human Validation: Provides a system for human review and approval of AI-processed information.

10. Patient Communication: Automates patient outreach through text and email, keeping patients informed about their care process.

Founding Team

The founding team of Tennr includes:

1. Trey Holterman (Co-founder & CEO): Studied Computer Science with a focus on Machine Learning at Stanford. Previously worked at HealthIQ and Strava.

2. Diego Baugh (Co-founder & CPO): Studied Computer Science at Stanford, focusing on Human Computer Interaction and Design. Previously worked as an automation engineer at Goldman Sachs.

3. Tyler Johnson (Co-founder & CTO): Studied Computer Science with a focus on Systems and Networking at Stanford. Previously worked as a lead engineer at Tanduo, building data workflows for large industrial companies.

Problem and Market Fit

Tennr addresses a significant pain point in the healthcare industry: the overwhelming amount of paperwork and administrative tasks that burden healthcare providers. This problem often leads to inefficiencies, delays in patient care, and increased costs for healthcare practices.

The company’s solution fits into the market by:

1. Reducing the time and resources spent on administrative tasks, allowing healthcare providers to focus more on patient care.
2. Improving accuracy in document processing, potentially reducing errors in patient information and billing.
3. Speeding up processes such as insurance verification and prior authorizations, which can lead to faster patient care and improved cash flow for practices.
4. Adapting to various sizes of healthcare practices, making advanced automation accessible to a wide range of providers.

Business Model

While not explicitly stated, Tennr’s business model likely involves selling its AI-powered automation system as a service to healthcare providers. This could be structured as a subscription-based model, where practices pay for access to the software on a recurring basis. The company may also offer additional services such as implementation, training, and ongoing support.

Funding and Runway

The most recent funding information available indicates that Tennr has raised an $18 million Series A round, led by Andreessen Horowitz (a16z). The exact date of this funding round is not specified, but it appears to be a recent development as of the content’s creation date.

Competitive Landscape

While specific competitors are not mentioned, Tennr operates in the competitive healthcare technology and automation space. Potential competitors could include:

1. Traditional healthcare software providers that are expanding into AI-driven automation.
2. Other AI-focused startups targeting healthcare administration.
3. Large tech companies developing healthcare-specific solutions.

Tennr’s competitive advantage appears to lie in its specialized AI model trained on a large dataset of healthcare documents and its focus on end-to-end automation of various administrative tasks.

Customers

The company mentions working with healthcare practices of all sizes, but specific customer names are not provided in the main content. However, case studies are mentioned for the following organizations:

1. Total Sleep Management: A sleep disorders center based in Longwood, FL.
2. BetterNight: A company focused on diagnosing and managing Sleep Apnea.
3. MGA Homecare: A provider of personalized homecare services.

These case studies suggest that Tennr’s solutions are applicable to specialized clinics, diagnostic services, and home healthcare providers.

Relevant News

1. Tennr’s $18 million Series A funding round led by Andreessen Horowitz (a16z) was recently announced, indicating growing investor confidence in the company’s approach and potential.

2. The company has been featured in several prominent publications:

   • Forbes (March 26, 2024): An article discussing Tennr’s plans to improve patient access to doctors.
   • Bloomberg (March 26, 2024): A piece about Tennr’s efforts to improve fax machine functionality in healthcare.
   • Axios (March 26, 2024): Coverage of Andreessen Horowitz’s investment in Tennr to address fax-related issues in healthcare.

These recent news items suggest that Tennr is gaining traction and recognition in both the healthcare and technology sectors, with a focus on addressing long-standing inefficiencies in healthcare administration.