Clinical AI advisor · Healthcare operations

Would a real clinician sign this?

I harden AI-health products and infusion-scale operations so the clinical story survives a credentialed nurse.

St. Petersburg, FL · Remote · Open to relocation · RN, FL + CA

In practice
  • Clinical nurse manager Ambulatory infusion
  • Nurses led ~20 RNs
  • Experience 10+ yrs · ER, oncology, infusion
  • Licensure RN — FL + CA
  • Product Obioma · NCLEX Next Gen

Portrait / 10s loop reserved — see asset brief.

Obioma — NCLEX Next Gen clinical-judgment platform

Obioma

Live floor

~20 RNsambulatory infusion

Infusion center

Always on

24/7self-hosted VPS

Agent stack

On air

DOAENpodcast + YouTube

Podcast

In build

ANCCCE courses

CE pathway

Two ways to hire me.

Clinical AI Advisory

I pressure-test the clinical-safety story and the eval framework until a credentialed nurse could sign the product.

$200 / hour · fractional · remote

Request advisory

Healthcare Operations

Capacity, throughput, staffing model, AKS/Stark audit, and a 90-day plan. I run an infusion center; I'll audit yours.

$5–15k / engagement

Request an ops audit

Closed-loop systems architecture is the method behind both — how the pieces talk to each other and where the loop actually closes. Not a third thing to buy.

What's actually built.

Obioma — Case Engine and clinical-judgment platform

Obioma

NCLEX Next-Gen clinical-judgment platform. Six-step NCSBN reasoning. AI tutor.

See Obioma

Live floor

~20 RNsambulatory infusion · St. Petersburg, FL

Owned problems

Staffing · throughput · capacity · AKS/Stark

Infusion center

Staffing, throughput, capacity, AKS/Stark compliance — on a live floor.

Stack

OpenClaw+ Rosie_OS · self-hosted VPS

Method

Closed loops, not dashboards

Autonomous ops

OpenClaw and Rosie_OS running closed loops on a self-hosted VPS.

The nurse who builds systems.

I'm a nurse who refused to let the job name me. Ten years across ER, oncology and ambulatory infusion taught me where care actually breaks. Now, running an infusion center, I isolate the binding constraint — staffing, capacity, documentation, a safety story that won't hold — then build the loop that closes it. I do the same for AI-health teams, where the stakes are identical: a real clinician has to sign it.

Building systems that buy back time.

Let's see if it signs.

Clinical AI advisory, operations audits — remote, or relocation-ready.