How MedAssist AI Achieved 94% Compliance Across 8 AI Systems in 6 Weeks

At a Glance

Product Portfolio

MedAssist AI develops AI-powered clinical decision support tools used by 150+ healthcare facilities across Europe, processing 2M+ patient interactions monthly.

The Complexity Problem

Autonomous Agents

Three of their most critical systems were autonomous agents built on CrewAI. Traditional compliance approaches didn't address agent-specific requirements.

Clinical Triage Agent
├── Symptom Analyzer Agent
├── Risk Assessment Agent  
├── Routing Decision Agent
└── Human Escalation Handler

Each agent makes autonomous decisions about patient care routing.

Agent-Specific Requirements

• Logging multi-agent decision chains
• Tracking inter-agent communication
• Capturing human oversight interventions
• Auditing autonomous actions

Interconnected Systems

Patient Interaction Flow:

Patient → Communication Bot → Triage Agent → Diagnostic Agent
                                    ↓
                           Care Coordination Agent
                                    ↓
                        Clinical Documentation AI
                                    ↓
                           Medical Coding AI

Compliance needed to cover the entire flow, not just individual components.

The Solution: Protectron

MedAssist's CTO discovered Protectron while researching compliance solutions for CrewAI. The Agent Audit Trail feature was the differentiator.

Why Protectron Was the Right Fit

CrewAI Agent Integration

from crewai import Agent, Task, Crew
from protectron.crewai import ProtectronCallback

# Initialize Protectron callback with healthcare-specific settings
callback = ProtectronCallback(
    system_id="clinical-triage-agent",
    environment="production",
    
    # Healthcare-specific configuration
    log_agent_thoughts=True,      # Capture clinical reasoning
    log_delegation=True,          # Track agent-to-agent handoffs
    log_collaboration=True,       # Record multi-agent decisions
    pii_redaction=True,           # HIPAA/GDPR compliance
    
    # Human oversight tracking
    human_oversight_required=["routing_decision", "escalation"],
)

triage_crew = Crew(
    agents=[symptom_analyzer, risk_assessor, routing_agent],
    tasks=[analyze_task, assess_task, route_task],
    callbacks=[callback]  # Full audit trail
)

What the Audit Trail Captured

Triage Session: TRG-2025-001234
├── 09:14:32 - Symptom Analyzer: Received patient input
│   └── Analysis: Identified 3 potential conditions
│   └── Confidence: 87%
│
├── 09:14:35 - Risk Assessor: Evaluated urgency
│   └── Risk Level: MODERATE
│   └── Reasoning: "Symptoms consistent with non-emergency..."
│
├── 09:14:38 - Routing Decision: Determined care pathway
│   └── Decision: Route to telehealth consultation
│   └── Alternatives considered: [ER, Urgent Care, Scheduled]
│
├── 09:14:40 - Human Oversight: Physician review
│   └── Action: APPROVED
│   └── Reviewer: Dr. [REDACTED]
│
└── 09:14:42 - Session Complete
    └── Total agents involved: 3
    └── Human interventions: 1
    └── Audit trail: Complete

ROI Calculation

Key Takeaways