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Since 2020, >$30Bn has flowed into verticalized EHRs, largely through PE transactions. Think athenahealth ($17B), Inovalon ($7.3B), ModMed ($5.3B), WellSky ($3B), NextGen ($1.8B), Nextech ($1.4B), Therapy Brands ($1.3B), and Experity ($1.3B). These deals rarely show up on VC radars, but they signal two important things. First, across most specialties, clinicians are still running core workflows on systems built more than a decade ago. Second, the largest software outcomes in healthcare over the past decade are generally not venture-backed!
At Primary, we’ve been more broadly thinking a lot about what the future of application software looks like and how AI will reshape SaaS. There’s already plenty of debate about systems of record becoming systems of action. This piece is not to debate that future. Instead, we want to imagine a future where existing systems of record are paired with, or in some cases replaced by, true systems of action. In healthcare, EHRs are the most natural place to start. We will be posting a handful of pieces on this theme in the coming months that go deeper on the market, the product, and potential business models shift enabled by AI.
To set the stage — taking on specialty EHRs is not for the faint of heart. The process of ripping out and replacing any system of record is brutal. Most providers genuinely dislike their EHRs, but they live inside them every day. The change management alone is enormous, and the perceived risk often outweighs the promise of incremental improvement. The standard venture playbook has been to build a point solution on top of an existing system of record, earn trust, and then slowly eat away at the core platform before (hopefully) making the swap. But, watching how the “AI scribe wars of 2025” are unfolding makes us skeptical that this will work at scale. Incumbents are willing to copy anything that starts to matter. See Epic, Athena, and many more examples.
Epic is the most egregious example of how quickly momentum can be shifted. For years, the Abridge-Epic partnership was the engine behind Abridge’s breakout growth. Epic’s Workshop program effectively created a sanctioned, first-of-its-kind path for Abridge to build deep integrations, co-sell alongside Epic, and access early customers inside the Epic network.
Earlier this year, Epic shut down their Workshop program right before announcing its own competing scribe product. The message was unmistakable. And now, we’re seeing the same dynamic emerge across other multi-product EHR platforms. As incumbents roll out their own native AI features, they not only close off third-party distribution pathways, but also undercut startups on price. Even if Abridge continues to ship a meaningfully better product, incumbents will always have structural advantages in distribution and pricing power. To be clear, we’re rooting for Abridge and the entire startup scribe category. At the same time, it’s hard to look at the market dynamics and not believe that a disproportionate share of enterprise value will ultimately accrue to the platforms that already sit at the center of clinical workflows.
This raises a harder question: what does it actually take to build durable value in this market? One possible answer is not to sit on top of the EHR at all, but to become the system that coordinates and executes work end-to-end. In practice, that does not mean waving away the complexity of being an EHR. Any credible “core operating system” must either natively include or tightly integrate the fundamental components of an EHR. The difference is not whether you store records, but whether the system is designed primarily to document work or to actively move it forward. Seat and documentation-based pricing in today’s EHRs reinforces incremental change, while AI-native systems will likely require pricing tied to outcomes or productivity.
Another possible answer is to actually build an EHR. Building a modern EHR today is easier now than at any point in the last decade. Development cycles are faster, infrastructure is cheaper, and interoperability standards and data export requirements have improved in certain parts of the market. More importantly, legacy systems are reaching the limits of how far they can be stretched. Many have layered decades of workflows, pricing models, and incentives that make meaningful re-architecture extremely difficult.
This is why we’re interested in exploring the question, “Are AI-native and agentic EHRs a good place to invest?” From what we’ve seen in the market, it’s very difficult for existing systems to contort themselves far enough to truly redefine how work gets done. At best, the incumbents can deliver incremental improvements or integrated point solutions (i.e. scribe). At worst, they simply bolt on decades-old workflow solutions without meaningfully shifting productivity.
AI now makes something else possible: systems of action that interpret context, decide what should happen next, execute tasks, and close loops on behalf of users. Perhaps you pair that with a business model that undercuts incumbents on price and taps into new revenue streams, and you can imagine a product that is ten times better at a tenth of the cost. As one physician put it, “Imagine if I could just focus on my patients and everything else was handled?” For clinicians and patients, that is not a marginal improvement. It is a step change.
So what are the right market dynamics?
As we consider this market, we are not here to argue that the venture opportunity lies in unseating Epic or Cerner. The hospital market is structurally protected by switching costs and cost fallacy. Epic, in particular, also benefits from being private and unconstrained from quarterly earnings pressure, allowing it to reinvest aggressively for the long term. The more compelling opportunity sits in ambulatory care, where the market remains fragmented and shaped by a long tail of legacy EHRs that have not reinvested as aggressively as Epic.
Across the 38 medical specialties and 89 subspecialties, most non-hospital owned clinicians still use vertical EHRs built more than a decade ago. The UX and UI are often akin to digital paper and hide deep architectural limits. Practice management, RCM, patient engagement, imaging, intake, analytics, and documentation sit under one brand, but rarely function as a single system.
If you ever want an unfiltered readout of how providers feel about their EHR, spend an evening on r/medicine or any specialty subreddit. You will find endless threads written by clinicians complaining about clunky interfaces, “note bloat,” billing workflows, and general “why does this thing hate me?!” energy. There is no shortage of pain.
But, finding real opportunity for systems of action means looking past generic frustration and into the structure of each specialty. So far, four dynamics stand out.
- Provider independence. A specialty must have enough non-hospital-owned practices to create a real market for software adoption. In many fields, consolidation into health systems removes purchasing autonomy entirely. Specialties like dermatology, ophthalmology, GI, pediatrics, PT/OT, urgent care, and behavioral health still have meaningful populations of independent or PE-backed groups that make their own tech decisions. These are also the environments where a new operational layer can be evaluated, purchased, and deployed without multi-year IDN procurement cycles.
- Competitive dynamics. Every speciality has multiple EHRs built for them, but not all markets are created equal. As examples, mental health has over 35 different verticalized EHRs, while specialties like dermatology are dominated by one software solution (ModMed with ~85% market penetration).
- Workflow complexity. Systems of action shine where messy, cross-system work dominates. Imaging coordination, pathology loops, protocol-driven care, prior auth, referrals, lab results, patient messaging, scheduling changes, and multi-party communication all fit this pattern. As we consider expanding the scope of an EHR, the ability to take on this work can meaningfully expand TAM.
- Administrative burden. In many practices, the true bottleneck is staff capacity, not clinician capacity. Intake, eligibility, benefits checks, documentation prep, coding, edits, denials, and follow up consume enormous time. Vertical EHRs may provide screens, but not relief. Similar TAM expansion dynamics are also at play here.
If a true venture-scale opportunity exists, it likely sits at the intersection of these factors, paired with a credible strategy for reducing switching costs. That may come from better data portability, improved migration tooling, purpose-built adapters, or even direct economic incentives to offset the pain of change. AI may not eliminate switching costs, but it can meaningfully compress them. In our view, an AI-native EHR is most compelling in a specialty that has a large base of independent providers, a more fragmented incumbent EHR landscape, and a higher degree of workflow and administrative complexity.
What we’re still figuring out
We’re far from having all the answers. A few key questions we’re still working through that we will explore in subsequent pieces:
- How do you reduce the switching cost for providers as much as possible? AI could be the key to “why now” here on the technical side, but is that really enough?
- What are the dynamics of an EHR product that is truly 10x better than an incumbent?
- Do you need to lean into business model innovation to make this feasible for a provider and investable for VC? Ex. providing the EHR software for free and monetizing on the back-end via pharma services, RCM, or owning other workflows
- What are the speciality “ontologies” that are most automatable and what will require a human in the loop?
If you are building in this world, we would love to chat. We deeply believe the next generation of vertical EHR companies will not look like the last one. Be on the lookout for additional pieces that go deeper into AI-driven business models and product.
Additionally a huge thank you to Brendan Keeler, Nikhil Krishnan, and JP Patil for their thoughts on this piece!