System Architecture

Homy OS: A Three-Layer Medical Intelligence Architecture

Deep-dive into the technical architecture powering clinical-grade AI coordination. Intake Engine → Reasoning Layer → Coordination OS.

Engineering-Grade Depth

Safety-First Design

20-Year Modularity

Three-Layer OS Architecture

A modular, scalable system built for clinical-grade accuracy and 20-year longevity. Click each layer to explore its technical implementation.

Intake Engine

Conversational Data Collection Layer

Multi-modal patient narrative capture system that transforms unstructured input into structured clinical data using adaptive questioning, NLP extraction, and medical ontology mapping.

Core Components

Conversational AI Interface (Voice + Text)

Adaptive Question Engine

Symptom Extraction Pipeline

Medical Ontology Mapper (ICD-10, SNOMED CT)

Data Validation & Normalization

Multi-language Support Layer

Data Flow Pipeline

Input

Raw patient narrative (voice, text, structured forms)

Process

NLP extraction → Symptom normalization → Ontology mapping

Output

Structured clinical data objects (symptoms, timeline, context)

Technology Stack

LLM: GPT-4 + Domain-Specific Fine-tuning

Speech-to-Text: Whisper API

NLP: spaCy + Custom Medical NER

Ontology: ICD-10, SNOMED CT, LOINC

Data Schema Architecture

High-level data structures flowing through the system (no sensitive PHI details).

Intake Data Schema

{
  "patient_narrative": "string",
  "symptoms": [
    "array of symptom objects"
  ],
  "timeline": "temporal sequence",
  "context": {
    "demographics": "object",
    "history": "array",
    "medications": "array"
  }
}

Reasoning Output Schema

{
  "triage_level": "enum (emergency, urgent, routine, self-care)",
  "differential_pathways": [
    "array of clinical pathways"
  ],
  "red_flags": [
    "array of critical findings"
  ],
  "confidence_scores": "object with confidence intervals",
  "recommendations": "array of evidence-based actions"
}

Coordination Action Schema

{
  "routing_decision": "string (provider type, urgency)",
  "scheduling": "object with time slots & resources",
  "escalation": "boolean + escalation pathway",
  "care_plan": "structured care delivery plan",
  "notifications": [
    "array of stakeholder notifications"
  ]
}

Safety & Monitoring Architecture

Multi-layer safety systems and real-time performance monitoring built into the architecture.

Human-in-Loop Design

Every clinical decision point requires explicit human review. AI proposes, humans decide.

Mandatory clinician review gates

Override capabilities at all levels

Decision audit trails

Fail-Safe Protocols

Multi-layer safety nets with red-flag escalation, uncertainty thresholds, and automatic fallback mechanisms.

98.7% red-flag detection sensitivity

Confidence threshold-based escalation

Automated safety monitoring

Regulatory Compliance

Built-in EU AI Act, GDPR, and medical device standards compliance from architectural foundation.

Risk management system

Transparency obligations

Technical documentation

Continuous Validation

Real-time accuracy monitoring, drift detection, and systematic revalidation cycles.

Live performance tracking

Clinical feedback loops

Regular benchmark audits

Real-Time System Monitoring

Triage Accuracy

92.4%

Target: ≥92%

Agreement with clinician ground truth

Red-Flag Sensitivity

98.7%

Target: ≥98%

Critical symptom detection rate

Response Latency (p95)

1.8s

Target: ≤2s

End-to-end intake to reasoning time

System Uptime

99.8%

Target: ≥99.5%

Service availability (monthly)

Hybrid AI Model Stack

Clinical-grade AI requires more than LLMs. Homy combines multiple AI paradigms for safety and accuracy.

Large Language Models (LLMs)

Use Case: Natural language understanding, adaptive questioning, symptom extraction from patient narratives.

Primary Model

GPT-4 with medical fine-tuning

Safety Constraint

Structured output validation

Rule-Based Clinical Reasoning

Use Case: Red-flag detection, clinical pathway validation, evidence-based guidelines enforcement.

Knowledge Base

ICD-10, SNOMED CT, NICE Guidelines

Engine

Custom rule engine + ontology reasoner

Machine Learning Risk Models

Use Case: Triage risk scoring, urgency prediction, outcome forecasting with confidence intervals.

Algorithms

XGBoost, Random Forest, Neural Nets

Validation

Clinical benchmark datasets

Hybrid Advantage: LLMs provide flexibility and language understanding, rule engines ensure safety and clinical validity, ML models deliver quantified risk assessment. The combination achieves 92.4% triage accuracy with 98.7% red-flag sensitivity.

20-YEAR ARCHITECTURE

Built to Last Two Decades

Homy OS is designed with architectural principles that enable continuous evolution without breaking changes. Modularity is not a feature - it's the foundation.

Layer Independence

Each layer operates independently with well-defined APIs and contracts

Long-Term Benefit

Individual layers can be upgraded, scaled, or replaced without affecting the entire system

Polyglot Architecture

Best-fit technology stack per layer (Python NLP, Go coordination, TypeScript UI)

Long-Term Benefit

Optimize each component with the most appropriate tools and frameworks

Event-Driven Communication

Asynchronous event bus enables loose coupling between system components

Long-Term Benefit

Resilient to failures, scalable under load, easy to extend with new services

Version-Controlled Models

All AI models versioned, tracked, and deployable independently with rollback capability

Long-Term Benefit

Safe experimentation, A/B testing, and rapid iteration without system-wide risk

Engineering for Healthcare's Future

Healthcare evolves slowly, but technology moves fast. Homy OS bridges this gap with an architecture that can absorb new AI breakthroughs, regulatory requirements, and clinical practices without requiring a rebuild. We're not building for today. We're building for 2045.

Architecture Diagrams

Interactive visual representations of Homy's system architecture with light and dark theme support.

System Architecture

3-tier architecture showing UI Layer → Service Layer → Data Layer with EU/UK compliance

Clinical Data Flow & Security

End-to-end encrypted data flow from patient to care team with GDPR/HIPAA compliance

Integration Ecosystem

HL7 FHIR-compliant integrations with EHR, EPR, Lab Systems, and Remote Monitoring Devices

Note: All diagrams support both dark and light themes for presentation flexibility. Each diagram is built with SVG for scalability and professional print quality.

Engineering-Grade Healthcare Infrastructure

Homy OS is more than software. It's a clinical-grade platform designed for accuracy, safety, and longevity. Interested in the technical details or integration possibilities?

View Investor Deck Clinical Safety Statement

Technical inquiries: hello@homy.health