Care that runs at night, and survives the audit.
Clinical AI fails on one of two things: it adds clicks, or it cannot be audited. This is the work of building something that does neither.
Every extra click is paid for by the most expensive person in the building.
Clinical teams are overwhelmed by electronic health record navigation and documentation. The standard response — buy a tool — usually makes it worse, because the tool arrives with its own login, its own screen and its own workflow.
And where AI is involved, security leaders are right to hesitate. Protected Health Information reaching an unvetted model is not a risk that can be remediated afterwards. Absent a governance framework, the safest answer is no, and that is the answer most of them give.
Sit with the clinic before writing code.
We do not sell generalized AI. We start with clinic leadership and the people doing the work, to find where the time actually goes — which is rarely where the org chart suggests.
Observe the real workflow
Where the minutes go during and after an encounter, not where a process document says they go.
Provision compliant infrastructure first
Heavily audited environments where clinical models can be trained without violating HIPAA or 42 CFR Part 2.
Build into the background
The system produces its output without asking the clinician to change what they do or open anything new.
Keep the human in the loop
Every AI-assisted output is physician-reviewable, and the review is part of the record.
Infrastructure that operates behind the encounter.
Ambient documentation that drafts notes in the background, and pre-billing chart review that catches unmapped codes before claims go out. Both run at sub-100ms latency, which is what makes them ambient rather than another thing to wait for.
What changes once it holds.
- 70% less documentation time. Measured against the clinic's own baseline, not a vendor benchmark.
- Zero additional clicks. The system requires no new screen and no change to how the clinician works.
- 100% auditable encounters. Every AI-assisted output traces to the model call that produced it and the clinician who approved it.
- Margin protected before submission. Pre-billing review catches unmapped codes and missed charges while they can still be corrected.
Where this has run.
-
Live in production · Healthcare
Three platforms treating real patients today.
24/7 physician-reviewed care for 39 conditions, a digital autism clinic providing live care for autistic children, and pre-operative 360-degree visualization for surgical patients — all three running in production, all physician-reviewed.
<100msAmbient latency70%Less charting time100%Auditable encounters39Conditions supported -
Next
Room for the next customer under this solution. Adding one is a new entry here, not a rewrite of this page.
Bring us the hard part.
Every one of these began as a diagnostic, not a deployment. If the problem above is yours, that is where we would start too.