When everyone is buying the same sensor, what's defensible?
Thoughts on where the moat has moved.
This is the companion to “How to tell a wearable moat from a head start.” That piece was for the people deciding whether to wire the check to fund the company. This piece is for the founders building those companies.
Nikhil Krishnan made an argument that the consumer health stack is commoditizing. Labs, records, telehealth, even AI primary care are swappable, and most of them burn cash on their own. His read is that wearables are the layer that holds up. They measure you objectively instead of asking you to rate your anxiety from one to ten. They tell you something is off before you go looking. And they earn on hardware margin and recurring software at the same time, right when software-only moats are eroding.
He is right about all of it. I want to push on the one word doing the heavy lifting, because if you are building one of these companies, “defensible” is hiding the decision that determines whether you make it.
The sensor is the most commoditized part of the entire stack.
The sensor is table stakes now
Dexcom and Abbott make the large majority of CGM hardware. Stelo, the first over-the-counter glucose biosensor, is resold under a dozen metabolic-health brands. Signos and Nutrisense run on it. The wrist is converging too, with Oura, Whoop, Apple, and Samsung chasing the same optical and electrical sensing. If your defensibility is the component, you are defending the one thing two device giants and several trillion-dollar platforms already make better and cheaper than you can.
Then the regulator widened the door. On January 6, the FDA rewrote its general wellness guidance. Non-invasive sensing of heart rate, glucose, blood pressure, and heart rate variability can now sit in the wellness lane with no clearance, as long as you avoid claims about diagnosis, disease, or clinical management. At Wilson Sonsini’s medical device conference this month, the pathway-and-enforcement-discretion question was on the main stage. The agency framed the change as removing friction for innovators. From a founder’s chair, it removed a wall.
That gift makes the layer more commoditized, not less. The clearance burden used to be the moat nobody talked about. It kept the look-alikes out. Now anyone can buy the sensor and ship the reading without a review. The barrier you were quietly standing behind just came down for you and for everyone chasing you.
A reading is not an action
If the sensor is table stakes and the raw reading is now license-free, what is left to defend? The interpretation that someone will act on.
There are exactly three buyers of an action: the person wearing the device, a clinician, and a payer. Each has a different bar, and only the second and third pay in a way that compounds.
The consumer pays for novelty, and for most products the loop goes stale and the band comes off. A rare few engineer retention well enough to make consumer subscription a real business. Most do not, which is why Signos just raised $20 million, per MedCity News, to push CGM past diabetes into weight loss on the back of GLP-1 demand. Read that as the consumer wedge searching for a stickier reason to exist. Glucose curves are interesting for a month.
The clinician does not distrust your data. A published survey of physicians on smartwatch cardiovascular data found they agree it is useful, then named the actual blockers: no billing code, and no time in the visit. The handle people reach for is the remote monitoring code family, RPM for device-supplied physiologic data and RTM for therapeutic data, built for exactly this. Here is the catch, and it is the whole argument in miniature. Those codes generally require the data to come from a device that meets the FDA definition of a medical device. The reimbursement handle sits on the far side of the same line you were tempted to stay behind. You cannot bill your way out of the wellness lane while you are standing in it. A code is the difference between a reading that dies in the inbox and a reading a clinician is paid to look at, and reaching it means crossing the line on purpose.
The payer pays for outcomes or cost offset, backed by evidence. The door here is opening, not open. Whoop’s $575 million Series G in March, at a $10.1 billion valuation, brought Abbott in as a strategic investor and Mayo Clinic as a clinical partner, per MedTech Dive. That is the consumer-subscription company with the retention everyone else envies, using its raise to buy a path toward the clinical and reimbursed side. Broad commercial coverage for consumer wearables is still thin and inconsistent, so read moves like this as early signals, not proof the door is open.
Two things a medical director will tell you on the first call. A billing code is necessary and not sufficient, because carriers can decline it, pay it poorly, or wrap it in prior authorization, and coverage is a separate fight from coding. And a payer does not reimburse an accurate reading. It reimburses a reading that, acted on, changes an outcome or lowers a cost, with evidence good enough to weigh against the current standard of care.
The trap hiding in the wellness lane
This is where the SaMD and wearable founder gets cornered, and it is a product decision long before it is a regulatory one.
The claims that keep you in the wellness lane are the same claims that make your data clinically unactionable.
To stay license-free, you say the words: for general wellness, not intended to diagnose or treat. That sentence buys you speed. It is also the reason a cardiologist cannot use your output to change a medication, and the reason a payer will not reimburse it. You bought velocity by promising your data does not matter clinically, and then your Series B story needs it to matter clinically.
Think of it as wiring versus paint. The wellness positioning is paint. You can repaint. The things that make data actionable are wiring, and you cannot rerun the wiring cheaply after you have shipped to a million wrists.
Two things are paint, the parts you can change later:
Wellness-only positioning and claims. You can reposition, but every claim constrains who can act on the data while it stands.
Consumer app, dashboard, and UX. Iterable and visible, and not what a clinician or payer relies on.
Everything that decides whether your data can cross into care is wiring, the parts you cannot rerun cheaply once you have scaled:
Analytical validity, the reading being accurate in a population that looks like your users. The floor for any clinical use, and slow to reconstruct after a consumer launch.
Clinical utility, proof that acting on the reading changes an outcome or lowers a cost. The expensive one, because it is the evidence a payer actually reimburses, and a different study from accuracy.
A named owner for clinical liability. Decides whether a clinician can act on your output at all.
Consent and data governance written for clinical use. Consumer consent does not cover clinical use, so a later pivot inherits a gap on data you already hold.
A reimbursement pathway, including RPM or RTM design. No code means no durable payer, and this shapes the product, not just the billing screen.
Wiring does not mean maximum spend. The cheap version is a regulatory and reimbursement strategy memo plus early payer input, low five figures in most markets, that keeps the clinical door open: the claims you avoid now, the consent language you adopt now, the single validation endpoint you design toward. The expensive version is a full clinical-utility study and a cleared indication. You do not need the expensive version today. You need to not foreclose it. The mistake that costs the most is skipping the cheap work, because that is what quietly locks the door.
If you already shipped
Half the people reading this already launched as wellness. You are not stuck. You are paying more to fix it later than you would have paid to build it now, which is a worse position, not a fatal one.
The moves that still work: amend your claims going forward, re-consent users for clinical use rather than assuming the consumer consent covers it, and run validation retrospectively on the data you already hold. The data you gathered as wellness can often seed the evidence you need for clinical use, but only if your consent and governance permit that use. That clause is the one most teams discover too late, usually in diligence, usually when a buyer’s counsel asks the question no one on the team can answer.
Data company or decision company
The split is simpler than the category makes it look.
A data company sells readings and dashboards. It competes with everyone who can buy the same sensor, which is now everyone. A decision company sells an action a clinician or payer will stand behind. It competes with almost no one, because almost no one builds the boring parts.
I watched this from the inside at AliveCor. We built the first FDA-cleared medical device accessory for the Apple Watch. The single-lead ECG was the thing everyone pointed at. Then Apple put an ECG in the watch itself. The sensor was never the moat. The cleared indication and the accuracy a clinician would rely on held longer, and even those were table stakes, not the finish line. Getting a physician to act on the read, and getting anyone to pay for it, was a separate climb from proving the read was accurate. That is the distance between analytical validity and clinical utility, lived rather than diagrammed. If your defensibility is the part the platform owner can absorb into their next release, you do not have a moat. You have a head start, and a clock.
What to do before your next roadmap meeting
Three questions, and you can run them this week.
First, for each headline metric on your device, name the buyer of the action. Not who sees the number, who acts on it and pays. Run it on a real one. A consumer CGM that says “see how meals affect you” has a buyer of the action who is the user, and the user churns. A CGM whose reading a clinician uses to titrate a GLP-1 dose has a buyer who is the clinician, if there is a code and a liability owner. Same sensor, different company. If your honest answer is “the user feels informed,” you are a data company. That can be a real business. Just decide on purpose, not by drift.
Second, list every claim you are making to stay in the wellness lane, and for each one write down what it forecloses. If a claim blocks the clinical or payer use you are counting on eighteen months out, it is not a marketing line. It is a strategic constraint you are accepting now to move faster today.
Third, sort your trust investments into wiring and paint using the list above, then check whether your build sequence funds the wiring before the scale or after. After is the default, and after is the trap.
The front door, and what it costs
Push it out one more order, because this is where the category is heading and where this series goes next.
The company that owns the interpretation, the routing, and the reimbursement does not just have a moat. It becomes the front door to care, the role the primary care physician used to hold. A recent analysis in JMIR makes exactly this argument, and points out that we have not applied to wearable platforms the antitrust and trust scrutiny we apply to physicians who control referrals. That is the prize and the exposure in one sentence.
For now the operator takeaway is smaller and more useful. Nikhil is right that wearables are the last layer standing. But the defense is not the thing on the wrist. It is whether anyone with a budget will act on what the thing on the wrist says. That has never been a hardware problem. It is a trust problem, and trust is the one part of this stack you cannot buy off the shelf and resell.
Three tools. One problem: your product is ready but the deal isn’t closing.
Pressure Test — Find out where your pitch breaks, before the room does. Free to start.
Healthcare Market-Fit Lab — Diagnose whether the market you chose can actually buy what you built.
Sold. Build Your Pilot Conversion Playbook — Build the positioning, documents, and pilot structure that get contracts signed.
All three are built on the same premise: stalled deals are structural problems. The pitch is usually the last thing that needs fixing.
Arvita Tripati is the Founder and CEO of Vahana Labs, a B2B strategy consulting firm helping healthtech and AI startups transition from pilot to enterprise contract. She has launched 30+ regulated AI-enabled products and worked with firms like the VA, Moderna, Gilead, NHS, and Bristol-Myers Squibb.