Somewhere in a medical office this morning, a biller put a headset on, dialed a toll-free number, and heard the phrase that defines an entire industry: "Your call is important to us. Please hold." Forty minutes later, she will have confirmed one patient's benefits. That is the job. That has always been the job. Standard Practice looked at that scene and asked an impertinent question - why is a human doing this at all?
The company sells something deceptively simple: a voice AI that makes phone calls to insurance companies. Not a chatbot, not a portal, not another dashboard begging for attention. An agent that picks up the phone, dials a payor, navigates the maze of "press 3 for claims," waits on hold without complaint, and then talks - in a human-sounding voice, in real time - to the representative on the other end. It handles claim follow-ups, verifies benefits, chases prior authorizations, and files EDI enrollments. The pitch on its homepage is refreshingly free of adjectives: "Automate outbound calls to insurance. Scale your team with technology and get paid more, faster."
To understand why that sentence matters, you have to understand the size of the problem hiding behind it. Roughly a third of American healthcare spending - by common estimates, on the order of a trillion dollars a year - goes not to doctors or drugs or hospital beds, but to administration. A large, grinding share of that is the phone call. Someone at the practice has to reach someone at the payor to find out whether a claim was received, why it was denied, what the patient's coverage actually says. It is repetitive, it is emotionally draining, and it does not scale, because there are only so many hours a human can spend on hold before lunch.
01 The pivot that became the point
Standard Practice did not arrive fully formed. It grew out of Nibble Health, an earlier venture from the same founders that chased a different corner of the healthcare-payments world and raised $8.5 million before the team changed course. Pivots are usually told as stories of failure. This one is better read as an education: building Nibble taught Steven Greene and Phil Markunas exactly how broken the plumbing of healthcare payments really is, and where the worst clogs sit. When they rebuilt, they aimed straight at the clog everyone hates - the payor phone call - and, by their account, shipped the core product in about four and a half months.
The founding pair is an odd, effective couple. Greene, the CEO, came up through investment banking at Goldman Sachs and carries a Harvard MBA - a man fluent in the language of money and the mechanics of getting paid. Markunas, the technical half, is a machine-learning engineer who could actually make a synthetic voice hold a conversation with a Blue Cross representative and not fall apart when the script went sideways. One knew precisely how the dollars move. The other knew how to teach a machine to move them.
What is striking about the pivot is how narrow they made the target. Nibble Health had chased the consumer side of healthcare payments - the patient's experience of paying a bill. That is a broad, seductive market, and a hard one. Standard Practice went the other direction entirely, toward a task so specific and so unloved that most founders would never dignify it with a company: the outbound call from a billing office to an insurer. Narrow problems are unfashionable. They are also where durable businesses tend to hide, because a narrow problem that is genuinely painful is one customers will pay to make disappear.
How one call actually works
Caption: The unglamorous ballet of a single claim - now danced by software that doesn't get bored.
02 Not a script - a listener
The temptation, with something like this, is to imagine a robocall: a flat voice reading canned lines until a human hangs up. That is exactly what Standard Practice is not. Insurance calls are unpredictable. Every payor runs its own menus, its own rules, its own detours. A script breaks on contact with reality. The company's agents are built to adapt - to answer an unexpected question, to follow a representative down a branch nobody wrote down, and to learn from each interaction so the next one goes smoother. The machine improves by doing the thing humans burn out doing.
There is a quieter benefit that surfaced in the company's early press, and it is the kind of detail that tells you something about how the founders think. Not everyone finds phone calls easy. For workers with speech impediments, or with the ordinary human anxiety that a high-stakes call to an insurer can provoke, the payor phone queue is a daily ordeal. By taking the call off their plate, Standard Practice quietly widened who can do the work - an accessibility story that arrived as a side effect of an efficiency one.
Caption: Four flavors of the same misery, each handed to a machine that doesn't mind.
03 The economics of patience
Here is the part that makes revenue cycle leaders lean in. You cannot hire your way out of the insurance phone queue. Each new caller you add is a salary, a desk, a training curve, and a hard ceiling of one call at a time. Standard Practice breaks that arithmetic. One agent can hold a hundred conversations simultaneously; it works at 3 a.m. as happily as at 3 p.m.; it takes no PTO and files no grievance about the hold music. The unit economics of "get paid faster" stop being about headcount and start being about software.
The bet underneath the product is that voice - not portals, not forms - is where the stubborn friction still lives. Plenty of healthcare admin has been digitized. But the payor call has resisted, because it requires improvisation, and improvisation was, until very recently, the one thing machines could not fake. Standard Practice is a wager that the moment has finally arrived: that a language model with a phone line can do the human part of the human work.
There is a second-order effect worth naming. When calls are cheap and abundant instead of scarce and expensive, practices can afford to make calls they used to skip. The small denial that wasn't worth a caller's afternoon, the benefits check that got waved through on a guess, the follow-up that fell off the list at 5 p.m. - all of them become economical again. A practice that automates the call doesn't just do the same work faster; it does work it previously could not justify doing at all. That is usually where the real money hides in revenue cycle: not in the claims you were already chasing, but in the ones you had quietly written off.
Caption: Simultaneous calls, side by side. The chart isn't broken - the gap is the whole business.
04 A small team, a large target
Standard Practice is still early. It is a lean shop - on the order of a dozen people - working out of 33 Irving Place in New York, and it has already drawn the attention of the outlets that watch this space, with coverage in Forbes, Bloomberg, and Politico. It sits in a crowded and fast-moving neighborhood: portal-automation tools, insurance-verification startups, and the old guard of outsourced revenue cycle firms all want the same budget line. What separates Standard Practice is the insistence on the call itself - the belief that the phone, not the form, is the last mile of getting paid in American medicine.
Whether that bet pays off will depend on trust as much as technology. Ask any billing manager and they will tell you: a call that gets the wrong answer is worse than no call at all. The company's whole proposition rests on an agent that is not just fast but right, and that learns from its mistakes faster than a new hire would. It is a high bar. It is also, if cleared, an enormous prize - because the thing they are automating is something no one, anywhere, has ever enjoyed doing.
Which brings us back to the biller in her chair this morning, headset on, forty minutes into a hold that decides one patient's coverage. In the world Standard Practice is building, she takes the headset off. The call still happens - it has to; the system demands it - but a tireless, timezone-agnostic agent makes it instead, a hundred of them at once, while she does the work that actually needed a human. The hold music still plays. It's just that nobody has to listen to it anymore.