Course library
Evergreen clinical AI diligence briefs
Short, researched briefs on the themes that keep coming back in health-AI diligence. Browse the full catalogue below. Reading a brief, its narration, notes, flashcards and quiz requires a free account.
- AI foundationsAvailable now
How LLMs Work: A Senior Investor's Guide to Language Model Mechanics
What a language model actually does, and which vendor claims the mechanics cannot support.
For: investor, health_system, vendor
Content requires an accountSign in to read - AI foundationsAvailable now
RAG for Healthcare Leaders: Grounding AI in Evidence
How retrieval-augmented generation reduces hallucination risk, and where it still fails.
For: investor, health_system, vendor
Content requires an accountSign in to read - AI foundationsAvailable now
Evals and Benchmarks: A Healthcare Investor's Guide to AI Due Diligence
How to read an eval suite and tell a real performance claim from a benchmark artifact.
For: investor, payer, health_system
Content requires an accountSign in to read - AI foundationsAvailable now
Agents and Tool Use: Autonomous AI Systems for Healthcare Investment Analysis
What agentic systems add over plain models, and the new failure and liability surface they create.
For: investor, health_system, vendor
Content requires an accountSign in to read - AI foundationsAvailable now
Diffusion Models: A Healthcare Investor's Technical Primer
Where generative imaging is credible in clinical workflows and where it is still a demo.
For: investor, vendor, health_system
Content requires an accountSign in to read - RegulatoryAvailable now
FDA SaMD Pathway: What Clearance Actually Proves
How to read a 510(k), De Novo, or PCCP claim and what it does not tell you about clinical performance.
For: investor, vendor, health_system
Content requires an accountSign in to read - RegulatoryAvailable now
Predetermined Change Control Plans for Adaptive Models
Why a PCCP is the single most valuable regulatory asset an adaptive-AI vendor can hold.
For: investor, vendor
Content requires an accountSign in to read - RegulatoryAvailable now
Clinical Decision Support: Regulated Device or Exempt Software?
The four-factor CDS test and where most vendors quietly fail it.
For: investor, vendor, health_system
Content requires an accountSign in to read - Clinical AI categoriesAvailable now
Ambient Clinical Documentation: Evidence, Economics, Escape Velocity
Separating documented time savings from vendor-reported satisfaction scores.
For: investor, health_system, vendor
Content requires an accountSign in to read - ReimbursementAvailable now
Radiology AI Reimbursement: NTAP, CPT, and the Cliff After
How radiology AI actually gets paid, and what happens when the temporary codes lapse.
For: investor, vendor, payer
Content requires an accountSign in to read - Legal & liabilityAvailable now
LLM Clinical Liability: Who Is Responsible When the Model Is Wrong
Mapping liability across vendor, health system, and clinician when a generative output causes harm.
For: investor, health_system, vendor
Content requires an accountSign in to read - GovernanceAvailable now
Model Governance: What a Credible Program Looks Like
The difference between an AI governance committee and an AI governance slide.
For: health_system, investor, vendor
Content requires an accountSign in to read - Clinical evidenceAvailable now
Local Validation and Model Drift Monitoring
Why external validation results rarely survive contact with a new patient population.
For: health_system, investor
Content requires an accountSign in to read - Clinical AI categoriesAvailable now
Sepsis and Deterioration Prediction: The Cautionary Category
What the Epic sepsis model episode taught buyers about vendor-reported AUROC.
For: health_system, investor
Content requires an accountSign in to read - Privacy & securityAvailable now
HIPAA, PHI, and LLM Vendors
What a BAA does and does not cover when prompts and outputs leave the building.
For: health_system, investor, vendor
Content requires an accountSign in to read - Data strategyAvailable now
Data Rights: Who Owns the Training Corpus
The asset that determines whether a health-AI moat is real.
For: investor, vendor, health_system
Content requires an accountSign in to read - Clinical evidenceAvailable now
Reading Clinical Evidence for AI Products
A structured way to grade an AI evidence package in under an hour.
For: investor, payer, health_system
Content requires an accountSign in to read - Payer strategyAvailable now
AI in Prior Authorization and Utilization Management
The fastest-moving payer AI use case and its regulatory exposure.
For: payer, investor, health_system
Content requires an accountSign in to read - Operations & RCMAvailable now
Revenue Cycle AI: Coding, Denials, and Real ROI
How to separate reproducible RCM savings from one-time cleanup.
For: health_system, investor
Content requires an accountSign in to read - Payer strategyAvailable now
Risk Adjustment and Value-Based Care Analytics
Where coding-intensity AI creates value and where it creates audit risk.
For: payer, investor, health_system
Content requires an accountSign in to read - Market structureAvailable now
EHR Platform Risk: Building on Epic and Oracle Health
The single largest structural risk in most health-AI investment theses.
For: investor, vendor
Content requires an accountSign in to read - CommercialAvailable now
Pricing and Contracting Models in Health AI
PMPM, per-clinician, per-study, and outcomes-based pricing compared.
For: investor, vendor, health_system
Content requires an accountSign in to read - CommercialAvailable now
Pilot Purgatory: Diagnosing Stalled Health-AI Deployments
Why 60-80% of health-AI pilots never convert, and the leading indicators.
For: vendor, investor, health_system
Content requires an accountSign in to read - GovernanceAvailable now
Algorithmic Bias and Health Equity Exposure
How bias shows up in deployed models and what documentation reduces exposure.
For: health_system, payer, investor
Content requires an accountSign in to read - RegulatoryAvailable now
ONC HTI-1 and Algorithm Transparency Requirements
The disclosure regime EHR-embedded predictive models now operate under.
For: vendor, health_system, investor
Content requires an accountSign in to read - RegulatoryAvailable now
State AI Health Laws: The Emerging Patchwork
How California, Colorado, Texas, Utah, and Illinois rules change go-to-market.
For: vendor, payer, investor
Content requires an accountSign in to read - Clinical AI categoriesAvailable now
Imaging Triage AI: Workflow Value vs. Diagnostic Value
Why time-to-treatment products sell differently than detection products.
For: health_system, investor, vendor
Content requires an accountSign in to read - Clinical AI categoriesAvailable now
Patient-Facing Conversational AI: Triage, Access, and Risk
Where patient-facing LLMs create measurable access gains, and their failure modes.
For: health_system, investor, vendor
Content requires an accountSign in to read - Privacy & securityAvailable now
Security Posture Diligence for Health-AI Vendors
A practical security read that goes beyond a SOC 2 logo.
For: health_system, investor, vendor
Content requires an accountSign in to read - Operations & RCMAvailable now
Build vs. Buy for Generative AI in Health Systems
When an internal platform beats a point solution, and the true cost of each.
For: health_system, investor
Content requires an accountSign in to read - Diligence processAvailable now
The Health-AI Diligence Checklist
Twenty-five questions to ask any health-AI target, and the answers that should worry you.
For: investor, vendor, health_system, payer
Content requires an accountSign in to read