During the first half of the year, $7.4B was quietly raised within the digital health sector across 244 deals; however, the current distribution of capital is far from uniform across health tech startups. Capital has become highly concentrated around the use of artificial intelligence technologies performing many of the deep clinical tasks that were once done by clinicians, which leaves only the basic consumer application space competing for what remains.
This guide provides insight into the direction of finance within the digital health industry, the major market trends driving that direction, and an analysis of those platforms that are producing actual operating results.
How Capital Flows into Health Tech Startups
Funding basic patient portals is no longer on the horizon. "Big" money investors, which comprise over half of all funding, are looking for results. In fact, approximately 45% of investments were made during the first half of the year in $100 million+ funding rounds. The median value of these investments increased to $14 million. The reason for this continued concentration is artificial intelligence.
As a result, buyers are looking for very specific tools that are designed to automate the full workflow of the clinical practice. Ambient documentation and revenue cycle engines are now the most heavily funded categories.
Hospital administrators are looking for hard numbers before making a purchase from health tech startups. They are looking for evidence of how much time has been saved by physicians using their product, fewer denied insurance claims, and a measurable reduction in missed appointments. If any product cannot prove its effectiveness in both time and money, it will not survive.
Market Trends Shaping Health Tech Startups
The digital health market is evolving in a few different directions. Small tools are losing prominence to the mega-platforms that allow us to manage all our daily tasks.
The Rise of Giant Platforms
Venture capitalists are taking fewer risks by pooling large amounts of cash into a single "sure thing." Rather than spreading their investments over a number of smaller companies, they've instead put $100M behind one successful business.
As a result, the market is moving toward a handful of mega-companies. Small businesses can either become fully integrated with major EMRs (like Epic) or they will not receive further funding. This reality is very difficult for startup founders, especially since the market now rewards size, safety, and revenue generation.
Smarter Tools Replacing Old Software
Last year, clinical AI received 54% of all health investment dollars and has continued to do so. It's all about execution now. Providers want to eliminate extra screens on their desks. They would prefer to have background collaborators who perform the work of gathering and documenting patient information.
Ambient documentation: Enables you to "listen in" to the interaction between the patient and provider in real time, reducing doctor typing time at night.
Coding and billing: The software will read the clinical note, assign the correct medical codes, and ensure the provider receives payment from the insurer.
Prior authorization: This is a tool that will automatically check with insurance carriers for eligibility before submitting claims and eliminate denials before they occur.
Patients Buying Care Directly
Mental health and obesity have proven to provide huge opportunities for growth within the healthcare industry. They are two of the fastest growing areas, based on consumer demand. Consumers are willing to pay a premium to gain quick access to quality healthcare.
Many new health tech startups are created from drugs that aid with weight loss, who provide the ability to prescribe, treat, and track their client’s progress in real time by using technology. Many companies are also returning to wearables providing smart rings and continuous blood monitoring systems with public offerings.
New Government Rules Force Tech Upgrades
New federal regulations are requiring hospitals to acquire improved technology for the submission of insurance pre-approval requests to insurance companies, effective January 2027. Currently, physicians wait for hours for responses from insurance companies via faxes and telephone calls.
This outdated and tedious process is being replaced with new regulations requiring immediate, electronic two-way communication between hospitals and insurers, as well as hospitals and other stakeholders. In addition, the requirement for the submission of electronic pre-approval requests has resulted in a surge in demand for automated pre-approval systems.
Leading Health Tech Startups and What They Do
The following companies are examples of those that are currently providing the greatest impact in clinics and hospitals.
1. OpenEvidence
OpenEvidence, an AI-driven medical search engine, is utilized by more than 40% of practicing physicians in the U.S. They recently closed a Series D funding round of $250 million.
OpenEvidence is not your average search engine; rather, it interfaces directly with the IT infrastructure of hospitals; they have signed major deals with high-profile institutions like Mount Sinai. OpenEvidence provides real-time, accurate medical answers directly to the physician at the time of decision-making.
2. Abridge
Abridge is a software solution within the Epic EMR system (which is a very well-established EMR); it is a documentation solution that combines ambient recording of physician/patient conversations with automatic clinical documentation generation.
The deployment of these services has reached over 100+ healthcare systems and to date have raised approximately $758 million in total funding. The time savings associated with these solutions is where the true value exists—through case studies, these types of solutions can document time savings of 81%, enabling a doctor to close a note in an average of only 43 seconds.
3. Commure
Commure focuses on automating the back end of the revenue cycle in healthcare. They develop software to automate billing, coding, and insurance verification.
To date, over 130 of the largest healthcare systems utilize Commure's platform. They are valued at approximately $7 billion by their investors. The value proposition they provide to healthcare system executives is the ability to recapture lost time and improve efficiency by reducing the amount of denied claims. They sell to large enterprises based on the volume of claims processed by their platform.
4. Aidoc
Aidoc focuses on developing clinical AI in radiology. The company identifies critical alert items, including strokes and blood clots, by scanning images through their AI system immediately following the time of the scan.
The company has raised several $150 million funding rounds. Hospitals utilize Aidoc's software to minimize the time to start treatment for patients. In addition to speeding up the start of treatment, the system will flag critical alert items allowing the physician to intervene before the patient's condition deteriorates.
5. Hippocratic AI
Hippocratic AI is focused on developing safety-tested AI communicators for patient communication. This technology does not diagnose diseases, but rather focuses on non-diagnostic functions.
These types of functions include: checking on a patient's recovery after discharge from the hospital, sending automated reminders to patients to return for follow-up, and providing support to human nurses so they can focus their time on caring for patients that need more complex medical care. The general pricing model mirrors the number of clinical hours saved by using the technology.
6. Latent
Latent raised Series A funding to help combat the overwhelming burden of dealing with prior authorizations. Doctors face extreme delays as they wait on insurance companies to authorize treatments before they can provide care to their patients.
Latent is automating the prior authorization process, making it easier for physicians who will have difficulty meeting the regulatory deadline of 2027; all health systems will need to upgrade their technology and operate within the new guidelines.
7. Trase
Trase provides an agentic automated solution for high-volume faxing workflows. Their most recent seed round raised $107 million.
At Duke Cardiology, their system was used to automate processing over 5,000 faxes a month. Their solution converts unstructured paper files into structured, usable digital files without the need for human typists.
8. Midi Health
Midi Health is a virtual clinic specifically for women in menopause and perimenopause. Midi Health was valued over $1 billion to become a unicorn company.
They help connect women to their plan providers, providing access to targeted care that traditional clinics do not provide for approximately 45 million women.
9. Neko Health
Neko Health has created a business model around physical locations utilizing advanced body scanning technology that serves as a preventative health assessment tool.
Patients receive a full-body scan and can detect early symptoms of disease and convert to a prepaid, annual membership at an 80% rate.
10. Clair
Clair is working on a wearable technology device focused on the female physiology and hormone cycle. Their device will be launching late in the year, and they also raised $11.6 million recently.
The device monitors changes in women's bodies to help them better understand their bodies and the effects of their hormones. There is an overall trend moving away from generic devices and toward health tracking with specific actions that can be taken.
11. Tennr
Tennr focuses on the beginning of a patient's journey. It automates referrals and insurance verifications by processing faxes and unstructured documents and analyzing large amounts of data into small amounts of info in order to get a patient into the doctor's office.
By quickly getting the right data, the intake process can continue on rather than stalling in the waiting room.
12. Viz.ai
Viz.ai simplifies and informs the care process in times of emergencies when time matters most.
They provide alerts to doctors when a patient suffers from stroke or an embolism, routing the medical teams automatically before the intervention time expires. This saves lives and improves the efficiency of hospitals.
13. Innovaccer
Innovaccer provides a unified health records system. It pulls patient record data from countless different systems and combines that data into one clean view of the patient's medical records.
It uses automated agents to connect clinical, operational, and financial records, allowing large hospital networks to see exactly what is being lost as a result of the financial and operational loss of patient care.
14. Well Health
Well Health provides a very large-scale communications platform between patients and healthcare providers. It integrates directly with EHRs to automate appointment reminders, automated follow-ups after appointments, and outreach to patients for missed care opportunities.
The overall operational metric is to reduce the percentage of patients who do not show up for their appointments, which helps generate revenue for hospitals by filling their schedules with patients.
15. Lyra Health
The healthcare platform Lyra Health sells mental wellness benefits directly to employers and supports clients with access to a curated network of therapists and online services such as telehealth.
The Next Step for Hospital Technology
The market has moved past generic claims, and hospital executives will not be purchasing software that has AI capabilities simply because it exists, but rather based on the ability of that software to improve a particular "day in the life" function of their operations. For a vendor to be successful, they must clearly demonstrate their integration with existing systems and provide return-on-investment (ROI) based on hard facts (ex: 50% decrease in missed appointments or 87% decrease in after-hours call volume).
To succeed in the future, health tech startups must offer a high amount of deployment support. Vendors need to employ engineers that can provide the technical expertise and support needed to troubleshoot the inherent messiness of hospital IT systems on-site.
The market will continue to concentrate on tools that provide accurate measurement of employee productivity and reduce liability associated with strict adherence to government regulations. Vendors attempting to sell a "pretty" dashboard or alert system will not survive; however, vendors that sell "time," "scale," and "revenue protection" will capture the lion's share of the market.
Common Questions About Hospital Tech
How do hospitals measure time saved by ambient documentation?
To determine the true speed of ambient documentation, health systems have changed how they evaluate and measure this efficiency. Hospitals are no longer willing to accept vague promises around increasing efficiency. They will continue to evaluate this speed by using strict time studies.
The core operating metrics they will evaluate include total number of minutes saved by a clinician, exact amount of time required to close a clinical note, and total decrease in after-hours screen time of each clinician. As a result, if a vendor cannot provide evidence of an 80% or more reduction in raw documentation time during the pilot phase, as a general rule, a deal will not move forward.
Where do tools fail when connecting to medical records?
The largest failure point between an AI software application and an existing EHR occurs when the software requires a clinician to switch between two different systems/windows or copy-paste from one system to another.
The only way to deploy quickly and efficiently is to integrate the AI software into the clinician's current workflow without disrupting the standard patient intake model.
Why do test programs stop before a full hospital rollout?
Clinical AI pilot programs generally stall due to the vendor's inability to provide adequate hands-on engineering support during the initial rollout process. Setting up a new software application generally requires detailed mapping of local clinical habits, a thorough review of all data in the system for HIPAA compliance, and a thorough engineering analysis of the way the application interacts with the existing EHR system.
As a result, a large percentage of clinical AI tools have been successfully tested in a pilot program with five doctors but fail when implemented in a hospital environment with the wide variety of workflows experienced. Therefore, vendors that do not provide adequately trained engineers on-site to manage transitions will continue to lose their competitive advantage.