Top 10 Rising Healthcare Startups to Watch in 2026

Healthcare software development in 2026 is less about pilots and more about production. Care delivery keeps moving across channels, and teams need tools that fit real electronic health records (EHR) workflows and hold up under security and compliance review. For instance, telemedicine popularity surged during COVID-19 and then settled into a stable “new normal,” with estimates ranging from roughly 13% to 17% of visits across specialties in some analyses. At the same time, hospital AI is becoming more concrete. In 2024, 71% of hospitals reported using predictive AI integrated with the EHR, up from 66% in 2023. Market forecasts reflect that shift. Depending on scope and methodology, projections put AI in healthcare startups anywhere from about $110B to about $208B by 2030. 

In this article, we highlight top AI healthcare startups that show where innovation is heading next. We explain how we picked these healthcare tech startups, what they do, why it matters, and what it means for the future of healthcare platforms, workflows, and patient engagement.

How We Selected the Top Healthcare Startups

There are hundreds of healthcare technology startups tackling everything from AI‑driven diagnostics to personalized medicine. We didn’t create a ranking based on funding or valuation. Instead, we picked companies that signal where innovation is heading. To make our list of top healthcare startups, each company had to show novel use of technology such as generative AI, advanced analytics, or cloud architectures; evidence of measurable impact in the form of better outcomes, less paperwork, or faster drug discovery; traction with health systems, insurers, or pharmaceutical partners; and a track record of responsible practices like HIPAA compliance or FDA clearance. 

Top Healthcare Startups to Watch in 2026 

These top healthcare startups for 2026 cover a mix of innovation areas, including AI, analytics, remote care, workforce development, and drug discovery.

Hippocratic AI

Hippocratic AI is one of the best healthcare startups. The company creates non-diagnostic AI agents for patient-facing and operational tasks. It has reported over 150 million clinical interactions, raised $126 million in a Series C round in 2025, and in early 2026, it bought Grove AI and started a life sciences unit.

What they do: Non-diagnostic agents support intake, outreach, chronic care workflows, and high-volume admin interactions, plus trial-related patient engagement.
Why it matters: It focuses on burnout and throughput without making a diagnosis, which makes it easier to use in places with strict rules.

Abridge

Abridge turns clinician-patient conversations into structured notes and revenue-cycle-ready documentation. It raised a $300M Series E in 2025 and has been adopted by 200+ health systems across many specialties and languages.

What they do: Ambient documentation that goes straight into EHR workflows and billing and utilization processes that happen later.
Why it matters: It shows how LLMs can reduce documentation load while staying usable in enterprise clinical settings.

Aidoc

Aidoc provides FDA-cleared imaging algorithms and a platform for deploying and governing clinical AI. In 2025, it raised $150M to expand aiOS (Aidoc’s proprietary platform) and develop a clinical-grade foundation model called CARE.

What they do: Imaging triage and care coordination tools, plus an “AI operating system” to manage multiple models in production.
Why it matters: Faster triage and stronger AI governance help reduce delays and make multi-model adoption realistic for hospitals.

Neko Health

Neko Health runs preventive scanning clinics that collect multimodal health signals and use machine learning (ML) to support same-day physician consultations. It raised $260M and plans expansion across Europe and into the U.S.

What they do: Full-body scans that generate large, consistent datasets across imaging and biometrics, tied to a clinical visit.
Why it matters: It pushes healthcare toward prevention and earlier detection, backed by standardized, high-quality data.

Biofourmis

Biofourmis offers a hospital-at-home and remote patient monitoring (RPM) platform that combines devices, AI, and virtual care operations.

What they do: Continuous monitoring with clinical escalation workflows to support higher-acuity care outside the hospital.
Why it matters: It helps health systems extend capacity and manage risk between visits, which is key for value-based care.

Stepful

Stepful trains allied health professionals through accelerated programs supported by AI-based learning tools. It raised a $31.5M Series B in 2024 and partners with health systems to help fill workforce gaps.

What they do: Online and hybrid training with coaching and job placement, designed to scale the supply of essential roles.
Why it matters: Workforce capacity is a hard constraint, and scalable training infrastructure is part of modern care delivery.

AgentAI

AgentAI applies ML and robotic process automation (RPA) to automate revenue cycle work across claims and payment operations.

What they do: Automation for eligibility checks, claim submission, payment posting, and denial workflows, with predictive signals for outcomes.
Why it matters: Revenue cycle management (RCM) is expensive and error-prone, and automation can improve cash flow while reducing admin burden.

Inato

Inato connects trial sponsors with community-based research sites to improve recruitment and diversity in clinical trials.

What they do: A marketplace model that helps match studies to sites based on patient populations and operational fit.
Why it matters: It addresses slow recruitment and non-representative trials by expanding access beyond academic centers.

Grow Therapy

Grow Therapy is one of the well-known mental health tech startups that provides practice infrastructure for therapists, including scheduling, billing, and payer-connected workflows. It raised an $88M Series C in 2024 and works with major insurers.

What they do: Tools that help clinicians run independent practices and participate in insured care more easily.
Why it matters: It increases mental health capacity by removing operational friction and aligning delivery with reimbursement.

Absci and Owkin

Absci focuses on generative AI for antibody design, while Owkin builds predictive AI for target discovery. In 2025, they partnered to co-develop therapeutic candidates using both approaches.

What they do: A combined pipeline that links molecule generation with target selection and validation signals.
Why it matters: It reflects a shift toward integrated AI drug discovery platforms that can shorten timelines and reduce costs.

Where Healthcare Innovation Is Heading

Top healthcare AI startups are all working on different problems, but they are all going in the same direction. Healthcare innovators are focusing on tools that make operations easier, fit into clinical workflows, and build trust in regulated settings. The trends below show what healthcare platforms of the future will need to do, from getting patients involved to running the back office.

AI that works inside clinical operations

The focus is moving away from flashy AI demos and toward systems that can do regular work. It’s not so much about showcase demos anymore; it’s more about AI that can handle real work every day. That includes intake, outreach, triage, coordinating imaging, and some parts of running clinical trials. Control is what makes it possible: clear limits on what the system can do, human review at the right times, and safe backups when the data isn’t complete.

Administrative automation becomes part of the care experience

Ambient documentation and revenue cycle automation both focus on one main goal: cutting down the time clinicians and staff spend on paperwork. Healthcare startups focus on note creation, coding support, prior authorization, and claims workflows because these steps have a direct effect on patient access, efficiency, and satisfaction. The most important thing for platforms is that clinical and administrative workflows are coming together. This means that product teams will need to closely link documentation, billing rules, and payer requirements.

Care expands beyond the hospital through continuous monitoring

Hospital-at-home care and remote monitoring are now more common as teams look for earlier signs and faster ways to help patients between visits. The main challenge is not collecting data, but using it to act with the right processes and staff. In the future, platforms should make it easier to connect devices, handle alerts well, and make it clear who is responsible for what. This helps doctors avoid getting too much information and makes sure that patients still feel supported.

Data-rich prevention and more inclusive research

Preventive scanning models and clinical trial marketplaces are working to improve data quality and speed up decision-making. Innovators are focusing on long-term patient data, better ways to find study groups, and wider access to research sites. So, in the future, healthcare platforms will likely focus more on data quality, consent management, and scalable ways to use different types of data, while still putting privacy and governance first.

How to Turn Healthcare Innovation Concepts into Real Products

Developing a healthcare product is a long process. Turning an early idea into something that actually works in clinics involves much more than just creating a prototype. When you look at the healthcare tech startups mentioned above, some common patterns appear.

Start with a clearly defined problem. Hippocratic AI focuses on non-diagnostic tasks such as intake, outreach, and triage, which are hard for clinicians to handle at scale. Stepful tackled the growing workforce shortage by offering data-driven training. Instead of creating general platforms, both companies identified a specific issue and built technology to solve it.

Build on a compliant and interoperable infrastructure. For new projects to succeed, they need to work with existing EHR workflows and follow HIPAA or FDA rules. Aidoc’s iOS app runs several algorithms and provides real-time monitoring. Abridge’s platform gives “linked evidence” so clinicians can review AI-generated notes. 

Combine AI with human expertise. In most cases, AI supports human clinicians instead of taking their place. For example, Hippocratic AI’s agents do not make diagnoses, so doctors are still in charge of care decisions. Abridge’s notes always link back to the conversation, and doctors review and approve them. Biofourmis combines remote monitoring with virtual care teams. The best AI healthcare startups design systems that keep human judgment central.

Iterate with data and feedback loops. Startups collect data to improve their models and processes. For example, each scan at Neko Health’s clinics gives them millions of data points that help them improve. Stepful uses AI to keep track of how well students are doing and change the content when necessary. Feedback loops like these make sure that systems stay safe and work well.

Partner strategically. Large health systems, insurance, and pharmaceutical companies add resources, data, and credibility. Partnerships help speed up adoption, as shown by Hippocratic AI working with UNC Health and Homeward Health, Abridge’s enterprise rollouts, and Absci and Owkin teaming up with pharmaceutical corporations.

Scale responsibly. As AI adoption accelerates, accountability needs to rise with it. Hippocratic AI’s acquisition of Grove AI is a useful reminder that healthcare often requires specialized models and rigorous safety testing. For CTOs, the practical takeaway is to bake in risk management, clear governance, and transparent documentation from the start, so scaling doesn’t outpace control.

As you consider building a new healthcare product, it helps to partner with a reliable vendor that is aware of the regulatory nuances, data architectures, and human‑centered design.

Beetroot has delivered projects ranging from mobile applications to IoT‑based telecare platforms. We help innovators move from idea to MVP and then scale to enterprise‑grade products.

The Innovation Patterns to Watch

The healthcare analytics startups we’ve discussed demonstrate that the future of healthtech is being shaped by a diverse set of innovators, ranging from generative AI healthcare startups like Hippocratic AI to training platforms like Stepful and drug discovery pioneers like Absci and Owkin. The main focus now is on agentic AI, end‑to‑end platforms, data‑driven preventive care, and a renewed emphasis on human capacity.

The lesson is clear: deal with real problems, build responsibly, and choose your partners wisely. There are many ways to take advantage of the opportunities, whether you’re updating an old system, looking into a new personalized medicine startup, or using a mental health tech solution.

If you’d like to talk about bringing an idea to life or need help navigating regulations and technical challenges, feel free to reach out.

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