Architecture
NeuroLab is documented here as a layered system: clients, backend API, AI service, and supporting infrastructure.
Source Of Truth
This page summarizes the architecture model used by the docs site. It does not assert that the service source code lives in this repository.
System Overview
The platform is described as four operational layers:
Client Layer
Client Applications
User-facing web apps
The docs site sits alongside the platform-facing applications and describes the supported workflows, setup, and reference surfaces.
Core Layer
Backend API
Backend service boundary
The backend is the primary HTTP boundary for users, appointments, uploads, reports, billing, notifications, and related workflows.
Inference Layer
AI Service
Analysis and inference service
The AI service covers EEG analysis, voice processing, report generation, and model-related endpoints under a versioned API prefix.
Infrastructure Layer
Supporting Services
Data, queueing, and storage
Supporting services include the datastore, queueing, and object storage layers that the backend and AI service depend on.
Current Service Boundaries
Backend Responsibilities
- authentication and token issuance
- application data persistence
- appointments, uploads, reports, billing, notifications, and chat workflows
- route groups summarized in the backend API reference
AI Service Responsibilities
- versioned API routing
- EEG analysis endpoints
- voice analysis endpoints
- report generation and model-related workflows
Integration Patterns
| Mechanism | Current Role | Notes | | :--- | :--- | :--- | | HTTP/REST | Primary application integration | Main client and service API surface | | OpenAPI/Swagger | Backend schema discovery | The backend API page points to the generated schema | | Versioned API routes | AI service contract | The AI service API is documented under a versioned prefix | | Queue-backed jobs | Background processing | Used for asynchronous analysis and report workflows |
Runtime Shape
Client applications
-> Backend API
-> AI service for analysis and inference
-> Data, queueing, and storage services
Architectural Notes
Important Distinction
Keep the architecture page aligned with the routes and pages that exist in this docs repository. Avoid adding directory-level claims unless the source code is actually present here.
What is stable
- backend route summaries and OpenAPI entrypoints
- AI service versioned API prefix
- docs app as a separate Next.js application
What is integration-sensitive
- queue-backed async jobs
- deployment assumptions across the documented setup pages