De-identify once. Use any AI. Stay HIPAA compliant.
The compliance layer that unlocks AI innovation
Contact: clint@medscrub.dev
The Healthcare AI Dilemma
What Clinicians Want
- ChatGPT for clinical documentation
- Claude for case analysis
- Gemini for research synthesis
- AI scribes, decision support, patient summaries
- Experiment with new models as they launch
"We want to use AI to improve patient care"
What Compliance Blocks
- No BAA with that vendor
- Legal review takes 6 months
- Too expensive ($$$/year per tool)
- Can't experiment with new models
- PHI disclosure risk = HIPAA violation
"We can't approve AI tools fast enough"
The Regulatory Landscape: Why Now
January 6, 2025: HHS Updates HIPAA Security Rule
First major update in 20 years explicitly addresses AI systems. Organizations must now include AI tools in risk assessments and implement vulnerability scanning, penetration testing, and 72-hour recovery requirements.
May 1, 2025: Section 1557 AI Enforcement Begins
Anti-discrimination rules for AI in healthcare take effect. Organizations must identify and mitigate AI bias risks, with OCR actively auditing AI decision-making tools.
2024 Enforcement Reality: Record Fines
22 HIPAA enforcement actions resulted in over $9M in fines. The new Risk Analysis Initiative alone handed out $900K in penalties in just 6 months (October 2024 - April 2025), with 168M individuals affected by healthcare data breaches.
How will you use AI safely and compliantly?
Traditional Approach: The BAA Treadmill
Negotiate BAA
3-6 months legal review
Premium Pricing
$108K/year for ChatGPT Enterprise vs $240/year for Plus
Wait for Approval
6-12 weeks procurement
New AI Launches
Better tool available, start over
The Five Critical Problems
Slow Time-to-Value
By the time you get approval for one tool, better alternatives exist. Innovation moves faster than legal processes.
Vendor Lock-In
Switching costs are massive. You can't easily move to better AI models without restarting the entire BAA process.
Innovation Bottleneck
Legal and procurement teams can't keep up with AI release pace. Every new tool requires months of review.
Legal Overhead
Compliance teams are drowning in contract reviews. Every BAA requires dedicated resources and extensive documentation.
Prohibitive Costs
Healthcare editions charge premium prices. Multiple tools mean multiple six-figure annual commitments.
The MedScrub Approach
One De-identification Layer. Infinite AI Tools.
Patient Data (PHI)
"John Smith, DOB 03/15/1985, MRN 123456..."
MedScrub De-identifies
99.9% FHIR accuracy, <50ms processing
Tokenized Data
"[NAME_1], [DATE_1], [IDENTIFIER_1]..."
Use with ANY AI
ChatGPT, Claude, Gemini, Perplexity—no BAAs needed
Why This Changes Everything
PHI Removed Before AI
No patient identifiers ever leave your control. AI never sees real data.
No Business Associate Needed
No PHI means no BAA required under HIPAA Safe Harbor compliance.
Instant Experimentation
Try new AI tools in minutes, not months. Use standard versions at consumer pricing.
Session-Based Re-identification
Restore original PHI in AI responses when needed for your workflow.
Engineering Leaders: Production AI Without HIPAA Risk
Leverage Consumer AI Within Your Stack
Challenge
You want to integrate ChatGPT, Claude, or Gemini into your product, but can't risk PHI exposure
What You Get
Drop-in API that de-identifies data before it reaches any AI model
Use Cases
Clinical documentation assistants, patient communication tools, diagnostic support features
Outcome
Ship AI features in weeks, not quarters. Use best-in-class models without vendor lock-in
Engineering Leaders: Protect Non-Production Environments
Stop Building In-House Scrubbing Solutions
Challenge
Dev, staging, and test environments need realistic data, but copying production PHI creates compliance nightmares
What You Get
Automated de-identification pipeline that maintains data utility while removing all 18 HIPAA identifiers
Use Cases
QA testing with realistic patient scenarios, developer sandboxes, demo environments, training systems
Outcome
Your team works with production-quality data without compliance risk or engineering overhead
Researchers: Safe PHI for ML & Analytics
Jupyter Notebooks, Desktop Agents, and Research Tools
Challenge
You need real patient data for ML model training, research analysis, and AI experimentation—but IRB approval and data access are bottlenecks
What You Get
De-identified datasets that preserve statistical relationships and clinical patterns while removing all identifiers
Use Cases
Training predictive models, exploratory data analysis in Jupyter, testing AI agents locally, research publications
Outcome
Accelerate research timelines. Work with realistic data in your preferred tools without months of approval processes
Healthcare Providers: Consumer LLMs in Patient Care
Use ChatGPT, Claude & Gemini Safely at the Point of Care
Challenge
Clinicians want to use powerful consumer AI for clinical notes, differential diagnosis, and patient education—but compliance says no
What You Get
Self-hosted 'Clipboard' web app and proxy API that automatically scrubs PHI before sending to any LLM, with seamless care coordination workflow and optional re-identification of responses
Use Cases
Care coordination, clinical documentation, case analysis, treatment planning, patient communication drafting, medical literature synthesis
Outcome
Clinicians get the AI tools they actually want to use, at consumer pricing, without HIPAA violations
Compliance Teams: Safeguard Inevitable AI Use
You Can't Stop It—So Make It Safe
Challenge
Your users are already using consumer LLMs with patient data. You know it's happening, but can't easily prevent it without blocking productivity
What You Get
Centralized de-identification layer with audit logs, usage monitoring, and policy enforcement across all AI tools
Use Cases
Shadow IT mitigation, compliance monitoring, audit trail generation, risk reduction without blocking innovation
Outcome
Transform unmanaged risk into managed compliance. Enable AI adoption while maintaining HIPAA controls and visibility
Technical Excellence: Production-Ready Infrastructure
99.9% Accuracy for FHIR
- 70+ FHIR R4 resource types supported
- 344+ explicit PHI field mappings
- Deterministic de-identification
- Bundle support with cross-reference preservation
- HIPAA Safe Harbor compliant—all 18 identifier types covered
99% Accuracy for Unstructured Text
- Multi-layer Entity Resolution:
- Internal algorithms (75-80%),
- spaCy NER (90-95%),
- Stanford BioBert (99%)
- Context-aware detection distinguishes clinical terms from identifiers
- All HIPAA identifiers: names, dates, addresses, phone, email, SSN, MRN, device IDs
Built for Healthcare
- Session-based re-identification: 24-hour default TTL, extendable to 7 days
- Performance: <50ms FHIR, <250ms text with minimal infrastructure.
Docker Self-Hosted
Complete control, PHI never leaves your infrastructure, built in UI
SMART on FHIR App
Q2 2026: Direct EHR integration with Epic, Cerner, Athenahealth marketplace distribution.
Roadmap: All Included in Your Perpetual License
Q1 2026: Expert Determination Certification
Market value: $50K+ annually. Keep actual dates, city-level geography, ages >89. Statistical risk analysis with <0.04% re-identification risk.
Q1 2026: Image Support (Proxy UI v2.0)
Q2 2026: System Clipboard 2.0 Interceptor App
Monitors system clipboard across all applications with real-time PHI detection and one-click de-identification. Works with EHRs, Slack, email—everywhere you work.
Q3 2026: SMART on FHIR App
Launch from Epic, Cerner, Athenahealth. De-identify directly from patient chart with one-click export to AI tools. EHR marketplace distribution enables enterprise sales.
Q4 2026+: Enterprise Features
Batch Processing API for thousands of records, HL7 v2 Support for legacy systems, Enterprise SSO (SAML 2.0, Okta, Azure AD), and all future features forever.
The Economic Case: Dramatic Cost Savings
3-Year Total Cost of Ownership Comparison
Cost of Ownership Savings
Save $134K-$314K over 3 years vs. competitors
Vendor Lock-In
Switch AI tools anytime with no penalties or additional costs
Unlimited Usage
No seat limits, no per-request fees, no annual renewals
What Your $10K Investment Includes
- Perpetual license—use forever, no renewals
- Unlimited users across organization
- Unlimited AI tools (any current or future)
- 99.9% FHIR, up to 99% text accuracy
- Self-hosted or cloud deployment
- Expert Determination (Q1 2026)
- Image support (Q1 2026)
- Clipboard interceptor app (Q2 2026)
- SMART on FHIR integration (Q3 2026)
- All future updates and priority support
Q1 2026 Early Adopter Pricing
$10,000
MedScrub Perpetual License
One-time payment. Use forever.
After March 31, 2026: $25,000
Everything You Get Today
Unlimited usage forever
No monthly fees, no renewals, no surprises. Unlimited users and AI tools across your entire organization.
Production-ready technology
99.9% FHIR accuracy, up to 99% text accuracy. Cloud API or self-hosted Docker deployment with enterprise security.
Complete roadmap access
Expert Determination, Image Support, Clipboard App, SMART on FHIR, Batch Processing, HL7 v2, Enterprise SSO—every feature we ever build.
Start Today (Zero Risk)
500 Free Credits
Try immediately, no credit card required
5-Minute Setup
Cloud deployment or <1 hour self-hosted
Real Results
Test with your actual clinical data
Why Lock In Q1 2026 Pricing?
Price Increase
Save $15,000 vs. post-Q1 pricing ($10K vs $25K)
Expert Determination Value
Worth $50K+ annually in the market, included forever
Future-Proof
All updates forever. Beat May 1 regulatory enforcement deadline.
Next Steps
Today
✅ Try MedScrub with 500 free credits
📧 Email cj@medscrub.dev with questions
🌐 Visit: medscrub.dev
This Week
🧪 Test with your clinical workflows
👥 Share with compliance, IT, clinical leadership
Before March 31, 2026
💰 Lock in $10K perpetual license pricing
🚀 Deploy to production
🎉 Start using AI safely across your organization
MedScrub AI Infrastructure for Healthcare