Prabhat Garg, M.D. — Clinical AI Strategy Advisor

How I help

For teams navigating a crowded, fast-moving AI market.

AI strategy & roadmap

Turn organizational goals into a prioritized, realistic plan — what to do now, what to defer, what to ignore.

Build-vs-buy & vendor selection

A physician who has actually built clinical AI assessing which tools to buy, which to build, and which waste the budget.

Clinically grounded prioritization

Separate the AI that meaningfully changes care and workflow from the AI that demos well and delivers little.

Compliant deployment

Stand up AI inside real HIPAA constraints — BAAs, audit logging, least-privilege access, incident response — from experience, not theory.

Clinical credibility for startups

A practicing-physician voice to pressure-test product, validate workflow, and build trust with clinician buyers.

Investor & diligence support

Expert perspective on clinical AI categories, hospital workflow, physician adoption, and product defensibility.

Proof, not theory

chartGPT

A deployed, HIPAA-compliant clinical-documentation SaaS on Google Cloud, built with AI-assisted development. Direct evidence that I can take clinical pain to a compliant, shipped product — which is why the strategic advice isn't hypothetical.

The system

Next.js frontend, FastAPI on Cloud Run
Firestore for PHI, Vertex AI / Gemini
Admin dashboard, per-token cost tracking
Terraform IaC, CI/CD

The compliance

Signed Google BAA
6-year audit-log retention
Least-privilege custom IAM, zero hardcoded keys
CVE remediation, incident response

The clinical moat

Hospitalist-authored prompt logic
Problem-based assessment & plan, ICD-10
Copy-forward safety, anti-fabrication guardrails
Clean EMR-paste formatting

The build is the evidence, not the offering. I use that technical fluency to give sharper strategic advice — I don't sell engineering labor.

Background

A decade of frontline medicine, leadership, and applied ML.

Hospitalist — Baylor University Medical Center

Aug 2020 – Present · Dallas, TX

Practicing physician at a 1,000-bed Level 1 trauma and tertiary referral center, managing the most complex medical and surgical populations: advanced heart failure / LVAD / transplant, hepatology, oncology, cardiothoracic surgery, and complex perioperative cases. Serve in pre-operative clinic optimizing high-risk surgical patients. Elected At-Large Representative to the Hospital Medicine Division Executive Committee (2023–2024).

Machine Learning Engineer / Data Scientist — UT Southwestern

2016 – 2017 · Advanced Imaging Research Center

Built CNN and RNN/LSTM models classifying MEG and fMRI data, achieving breakthrough accuracy in automatic artifact detection without reference EOG/ECG channels. Co-authored peer-reviewed work (MICCAI, PRNI).

Chief Resident — Baylor Scott & White Health

2017 – 2020 · Round Rock / Austin, TX

Selected to lead the internal medicine residency. Founded and led the COVID-19 Residency Taskforce; served as Epic EMR transition lead. Quality-improvement work with real financial stakes:

CHF 90-day readmissions — Medicare pilot with live financial penalties. 1st-place poster; accepted to National ACP.
Inappropriate telemetry reduction — system-wide order-renewal overhaul. 1st-place oral presentation.
Chest-pain length-of-stay — multivariate analysis safely reducing low-risk stress testing. Selected for oral presentation.

The physician in the room
who has also shipped the product.

Still practicing

Shipped clinical AI