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Local AI Healthcare Blog
Use these articles to understand private healthcare AI architecture, pilot planning, and workflow-specific decisions before you shortlist tools or commit to a deployment path.
What you will find here
Read the practical guide first if you want a quick, structured introduction to testing local AI safely inside a healthcare setting. Open guide →
Use the architecture piece when your team is already thinking about hardware, deployment shape, and multi-workflow private infrastructure. Open article →
The privacy-first adoption framework — six pre-procurement decisions that protect compliance posture before the demo, and the three demo moves that filter vendors by data path. Open article →
The UCLA NEJM AI RCT, Explained
What the 2025 ambient-scribe trial actually measured, why the 9.5% vs −1.7% split matters, and how to put the result into your RFP without overweighting one paper.
Read article arrow_forwardCanadian Hospital AI Procurement in 2026
What changed between 2023 and 2026 — Law 25 enforcement, PHIPA modernization, PIPEDA's AI-consent amendments — and how the 2026 procurement timeline differs from the 2023 playbook.
Read article arrow_forwardPrivacy-First AI Adoption
Evaluate AI vendors without exposing PHI during the demo. Six pre-procurement decisions and three demo moves that flip the procurement choreography.
Read article arrow_forwardThe 30-Day Private AI Pilot
Week-by-week playbook for running a structured 30-day private AI pilot — pre-week scope, shadow mode, clinician-supervised review, and the decision gate at the end.
Read article arrow_forwardOn-Premise Clinical Assistants
A reference stack for running the clinical scribe, discharge drafter, shift handoff, and document Q&A on hardware you own. Hardware budget, risks, and evaluation metrics.
Read article arrow_forwardLocal AI in Healthcare
A practical 30-day roadmap to test open-source local models safely, then scale with healthcare-specific guardrails.
Read article arrow_forward