Healthcare software breaks differently
Why HIPAA, clinical workflows, and AI in care don't forgive the shortcuts that pass elsewhere.
The first time a build I was on touched real patient data, I learned that "move fast and break things" is a sentence you can't finish in healthcare.
Most software fails in small ways: a slow page, a dropped event, a bug you patch on Monday. In healthcare those same failures land harder. A billing error becomes a claim an insurer rejects. A workflow that doesn't match how a nurse works gets worked around, and the data you were counting on stops meaning anything. A HIPAA gap is the worst of them: it's exposure you can't take back.
That's why we treat healthcare as a specialty rather than a vertical we dabble in. When we rebuilt a chronic-care platform an offshore team had left broken, the basic CRUD was the easy part. The hard part was everything that punishes a shortcut: a billing engine that produces the CPT codes insurers accept across eight care programs, clinical protocols that ask the right questions for a given patient's conditions, and a HIPAA-aligned backend with the encryption, access controls, and audit trails real patient data requires. Get any of those subtly wrong and the bug doesn't surface in a demo. It surfaces in a clinician's workflow, an auditor's review, or a denied claim.
AI makes all of this harder. We built AI into that platform: protocols that generate patient-specific questions, voice agents that talk to people over the phone. It's powerful, and it's exactly where "plausible but wrong" does the most damage. An AI that asks a slightly wrong clinical question can put a patient on the wrong path. That work needed senior judgment most of all: someone deciding what the model is allowed to do, and where a human stays in the loop.
This isn't an argument for being slow. We shipped that platform, scoped for a full year, in under nine months, with a four-person team and no in-house engineers for the client to hire. Speed and care can hold together, but only when the speed comes from people who've already seen how these systems break, rather than juniors moving fast through a domain that punishes what they don't yet know.
If you're building in healthcare and it has to be right (HIPAA, clinical workflows, AI in care), that's the work we know best.
If you've got a build that has to hold up, that's the work we do.
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