19 years of ops. No filter. No theory.
No content written for the algorithm.
These are frameworks built from real deployments, real failures, and real fixes — written for founders and operators who are building the hard way and do not have time for advice that has never been tested under pressure.
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The Healthcare Workers AI Is Changing Fastest Are the Ones Nobody Is Asking
Everyone is watching the clinical layer. Nobody is watching the operational workforce being transformed beneath it.
The Seven Metrics Every MedSpa Owner Should Track Weekly
If you cannot quote your no-show rate, your average lead response time, and your cost per booked consult — your operation is not under control.
Audit-Ready SOPs in Three Days — The Fortune 4 Template
The structure auditors expect, the language they reward, and the version control approach that survives staff turnover.
NMSDC and WOSB: Positioning a Healthcare Consultancy for Federal Contracts
Certifications open doors. They do not write proposals. The three things most MBE firms get wrong on the way to their first GovCon win.
HIPAA-Aware AI: What 'Compliant' Actually Means at the Architecture Layer
The phrase 'HIPAA-compliant' is doing a lot of work in vendor pitches. Here is how to vet whether a data flow would survive a real audit.
The voice behind the work
Tarean Thompson
Founder & COO, Geaux Uptown Solutions
19 years inside Fortune 4 healthcare distribution, Parkland Level 1 Trauma, and Walgreens leadership. Now builds the operational backbone funded health-tech startups never had time to build themselves.
Field-tested. Practitioner-written.
Every essay here is written from inside the work — not synthesized from second-hand research. If a framework appears on this page, it has been deployed in a real operation, with real consequences, and survived.
- →No AI-generated filler
- →No recycled vendor talking points
- →Sourced from 19 years of operational scar tissue
Healthcare AI intel. Every other Tuesday. No noise.
Field notes from inside live deployments. What is working. What is not. What is coming. Written by the operator doing the work — not a content team summarizing someone else's research.