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+# Architecture Overview
+
+**Hybrid AI + Edge SCADA for Small Water Systems**
+
+## Core Principles
+
+- **Local First**: As much processing as possible happens on the edge device.
+- **Low Egress**: Healthy state = highly compressed summaries. Only alerts carry rich context.
+- **Hybrid Intelligence**: Small models on edge for real-time decisions + larger models for complex reasoning and onboarding.
+- **Monitored Objects** as the central abstraction.
+- **Multi-Tenancy** with clear RBAC (Owner, Operator, User, Field Tech).
+
+## High-Level Components
+
+1. **Edge Device** (Raspberry Pi + Cellular)
+   - Local real-time signal processing
+   - Local web UI for setup (hotspot mode)
+   - Camera support for analog sensors
+   - eSIM / cellular connectivity
+
+2. **Cloud / Server Layer**
+   - Multi-tenant web application
+   - Dashboard (Basic + Advanced modes)
+   - Alert management and history
+   - Operator multi-system view
+   - Strong model for complex tasks (onboarding interview, anomaly detection, recommendations)
+
+3. **AI Model Strategy**
+   - Small specialized models on edge
+   - 9B-class model for personality/continuity and triage decisions
+   - Larger models (30B+) for complex reasoning and onboarding
+
+## Data Flow
+
+- Normal operation: Edge summarizes and uploads compressed data every 30-60 min
+- Alert condition: Edge sends rich payload immediately + triggers notifications
+
+**See**: `specs/` folder for detailed specifications.
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