Teardown: Project Med Pulse.
Architecting autonomous medical triage without compromising compliance. We bypassed standard, insecure SaaS tools to engineer a military-grade, HIPAA-compliant ecosystem utilizing self-hosted n8n orchestration, Agentic AI (MCP), and encrypted AWS Vaults to securely route international patients to the correct specialists.
Public AI Models Are a Massive Medical Liability.
Before iHexe, the client's medical tourism platform relied on an army of human coordinators to read sensitive MRI reports, translate patient inquiries, and manually book hospital beds across borders. The delay cost them critical cases. When they attempted to automate triage using off-the-shelf AI chatbots, their compliance officers immediately halted the project—sending raw patient records to OpenAI or Anthropic’s public servers is a direct violation of HIPAA and GDPR data residency laws.
DOB: 1982-11-04
SSN: 991-00-4821
DOB: [REDACTED]
SSN: [REDACTED]
Status: EMR UPDATED < 2.5s
The iHexe Clinical Protocol
Agentic AI Triage & PHI Sanitization (MCP)
We engineered cognitive triage without the legal risk. We deployed a custom Python Model Context Protocol (MCP) server within the client's private AWS subnet. When a patient uploads a medical file, our local MCP layer aggressively scans and redacts all PHI (names, SSNs, addresses) before passing the anonymized clinical data to the LLM for specialist matching. The AI predicts the required orthopedic or oncology department, and the MCP reconstructs the encrypted payload internally.
Encrypted n8n Orchestration
Healthcare logistics require military-grade routing. We completely avoided public Zapier/Make integrations. Instead, we deployed self-hosted n8n directly inside the client's Virtual Private Cloud (VPC). When the AI agent determines the correct hospital, an n8n webhook securely intercepts the decision, translates it into HL7/FHIR healthcare standards, and instantly updates the destination hospital's Electronic Medical Record (EMR) system over a heavily encrypted TLS 1.3 tunnel.
The AWS HIPAA Vault & DB Isolation
Data must be mathematically inaccessible to unauthorized actors. We architected the underlying PostgreSQL database utilizing AWS KMS (Key Management Service) for AES-256 encryption at rest. Every patient profile, visa application, and surgical schedule is cryptographically isolated. Even if a server breach occurred, the extracted data would be useless cryptographic noise.
# Python Model Context Protocol (MCP) Server: Local AWS Subnet PHI Redactor # Utilizes Microsoft Presidio Analyzer & Anonymizer to strip PHI before LLM Context from presidio_analyzer import AnalyzerEngine from presidio_anonymizer import AnonymizerEngine from presidio_anonymizer.entities import OperatorConfig from mcp.server import Server# Anonymize PHI with secure placeholder masks anonymized_result = anonymizer.anonymize( text=raw_report_text, analyzer_results=results, operators={ "PERSON": OperatorConfig("replace", {"new_value": "[PATIENT_NAME_REDACTED]"}), "DATE_TIME": OperatorConfig("replace", {"new_value": "[DOB_REDACTED]"}), "US_SSN": OperatorConfig("replace", {"new_value": "[SSN_REDACTED]"}), } )return { "sanitized_clinical_text": anonymized_result.text, "phi_entity_count": len(results), "compliance_status": "HIPAA_SAFE_0_PHI_LEAKS" }
Ready to Deploy HIPAA-Compliant AI Triage in Your Healthcare Platform?
Protect patient PHI, automate HL7/FHIR EMR integration, and bypass public LLM compliance risks with iHexe Healthcare Systems Engineers.