AI for healthcare, built for the 5–100 person shop.
Practices, clinics, and wellness businesses: places where the front desk carries the whole operation and the paperwork grows faster than the patient list.
Where does AI actually pay in healthcare?
Three places, in our experience. These are the clearest wins we see in practices like yours, not results we promise. None of them touch clinical judgment, and all of them start with the question every practice should ask first: where does the data go? We answer that plainly in Where Your Data Goes.
The calendar fills itself instead of the phone line.
Phone tag, no-shows, and gaps the front desk discovers too late to fill. An automation drafts confirmations and reminders, offers open slots when someone cancels, and keeps the day full. The front desk approves what goes out.
The paperwork is done before the patient sits down.
An intake agent collects forms and history ahead of the visit, chases what is missing, and hands staff a clean, chart-ready summary. Your clinicians spend the visit on the patient, and every clinical call stays theirs.
The claim is drafted from the documentation, not from memory.
Coding and claims work piles up at the end of the day and the denials pile up after that. An agent drafts the codes from the documentation and flags the uncertain ones for a person to review, so the biller stays accountable for every claim that goes out.
For most practices the right first move is the AI Readiness Audit: two to four weeks mapping where the hours actually go, and where patient data can and cannot go, before anyone builds anything. Pricing is published, in plain numbers: audits run $3,500–$8,500; sprints $12,000–$45,000, fixed quote in writing. The cloud-versus-on-prem decision, in plain English: where your AI data actually goes.
One build, drawn to scale.
Of the example builds on our homepage, this is the one that maps most directly onto the front-desk and intake work of a practice.
Qualifies the request before a person touches it.
Reads the incoming email or form, asks for the details that are missing, and routes the job to the right person with a clean summary attached.
The win: every request arrives qualified, summarized, and routed before a person reads it.Illustrative builds, not client claims. What we’d actually scope is whatever your free assessment shows is worth automating first. The one build we can name is MARCUS, a private AI back office for a regulated lender.
AI for healthcare practices.
Want the numbers?
The full price list is published — audits, sprints, managed services, all on one page.
Read the price list →01What can AI do for a healthcare practice?+
Typically the front-desk and intake work — scheduling, forms, and summaries — handled so a person reviews rather than retypes.
02Where does our patient data go?+
Where it needs to stay. The MARCUS build for a regulated lender runs entirely in-house, with no file leaving the building — the same control is available to you.
03How much does it cost?+
The AI Readiness Audit runs $3,500–$8,500; an AI Implementation Sprint runs $12,000–$45,000, quoted fixed in writing before work begins.
04How long does it take?+
An audit is 2 to 4 weeks; a build is 4 to 12.
05Do you work remotely or on-site?+
We run two hubs — Denver, Colorado and Phoenix, Arizona — for in-person work, and we work remotely with businesses across the US. Same method, same fixed prices either way.
See the wins in healthcare.
30 minutes with a senior advisor who walks your scheduling, intake, and coding workflows and tells you what is worth automating, and what is not.