Healthcare automation
We automate the processes that only function because people are absorbing them, at diagnostic and pathology laboratories, provider organizations and payers. Revenue cycle is where our deepest proof sits, and the method is the same wherever work is repetitive, rules-bound and document-heavy.
Book a teardownThe short answer
Any process where the steps are knowable, the inputs arrive in a predictable shape, and a person is currently acting as the connection between two systems. That describes a great deal of healthcare administration.
We do not lead with a technology, because the right answer varies. Sometimes it is rules-based automation, sometimes document understanding, sometimes an integration that should have existed years ago, and sometimes it is redesigning the process so most of the work disappears. What follows is organized by problem shape rather than by tool.
Our recommendation, unprompted
If you still have a meaningful volume of copy-between-two-screens work, automate that before you build AI capability. It is cheaper, more reliable, and the return is not speculative. We will tell you this on the call even when the AI work would bill at a higher rate.
Worked examples
Three engagements, each answering a different version of the same question: what happens when the manual version stops scaling.
Revenue cycle · service
Prior authorization automation
The deepest proof we have: a 300% capacity gain and 40% fewer denials, still running eight years later. Submission, status chasing and rework, handled consistently.
See the service →Clinical operations
Case assignment and subspecialty routing
Proof the method holds outside billing: scheduling work that has to respect availability and clinical judgment.
Read the case study →Denials · service
Denial management automation
Triage by what is recoverable, appeal packets assembled from the documentation the payor actually asks for, and root causes fed back upstream.
See the service →Not sure which of these describes you? The eight-question readiness check takes two minutes and points you at the right one, and the ROI calculator puts a number on what the manual version costs.
How the work splits
Most of what we do
Workflow automation
Rules-based automation, document capture and system integration applied to high-volume administrative work.
Right when you have significant deterministic manual work. Cheapest, fastest, and the return is not speculative. Start here.
Where it earns its place
AI-assisted workflows
Making unstructured documents usable, and drafting work a person then approves. Where AI fits is a narrower question than the market suggests.
Right when the remaining work is document-bound and judgment-adjacent, or you have a mandate and no safe path yet.
The honest comparison
You have other options, and some of them are better than us for some problems. Here is where each one wins.
Measured at a national cancer diagnostics laboratory, 2018 to 2026, against the client’s pre-automation manual workflow. See how.
By organization type
The method is the same everywhere. What differs is where the defects originate, and that decides where automation should start. If neither of these describes you, the teardown still applies.
For diagnostics laboratories
Lab billing breaks upstream
You bill high volumes of low-dollar claims against orders written by people who do not work for you. That single fact drives most of what goes wrong.
See the lab view →For provider groups
Denials created at the front desk
A rushed registration, an unverified plan, a referral nobody tracked. Adding billing staff adds rework capacity rather than removing the cause.
See the practice view →Next step
Tell us what is slowing your organization down. We come back with whether automation can fix it, roughly what it would take, and an honest answer when the tool is wrong for the job.
Book a teardown