feat(boc): Complete Business Operations Center v1.0

- Go backend API with full CRUD for all modules (CRM, Sales, Finance, HR, Legal, Marketing, Support, Purchase, Inventory, Projects, Automation, Analytics)
- Rust analytics service with parallel report generation
- C runtime with POSIX shared memory IPC
- PostgreSQL schema with 30+ tables, full migrations
- Redis cache, sessions, pub/sub
- Kafka event streaming with Zookeeper
- WebSocket hub for real-time updates
- Automation engine with cron jobs, workflows, event triggers
- JWT authentication, multi-tenant from start
- Docker Compose with all services
- Nginx reverse proxy with rate limiting
- Integration tests passing
- Feature gap analysis against Fortnox/Odoo/Visma

Refs: BOC-001

vims-core/instances/satellite-validation/README.md

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+# Satellite vs Ground Truth
+
+VIMS instance for satellite-validation.
+
+## Related Article
+[/insights/field-intelligence-vs-satellite/](https://landvex.com/insights/field-intelligence-vs-satellite/)
+
+## Anomaly Classes
+- resolution_mismatch
+- temporal_gap
+- cloud_obstruction
+- classification_error
+- change_undetected
+
+## Quick Start
+
+1. Add training images to `data/raw/`
+2. Annotate using LabelImg (YOLO format)
+3. Run preprocessing: `python src/detector.py`
+4. Train model: `python src/detector.py --train`
+5. Run inference: `python src/detector.py --predict data/test/image.jpg`
+
+## API
+
+Once deployed, access via:
+- REST: `POST /api/satellite-validation/predict`
+- WebSocket: `ws://host/ws/satellite-validation/alerts`

vims-core/instances/satellite-validation/config.yaml

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+# satellite-validation configuration
+
+topic: satellite-validation
+display_name: Satellite vs Ground Truth
+article_url: /insights/field-intelligence-vs-satellite/
+
+anomaly_classes:
+  - resolution_mismatch
+  - temporal_gap
+  - cloud_obstruction
+  - classification_error
+  - change_undetected
+
+model:
+  base: yolov8n.pt
+  input_size: 640
+  
+training:
+  epochs: 100
+  batch_size: 16

vims-core/instances/satellite-validation/src/database.py

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+"""
+Database setup for Satellite vs Ground Truth
+"""
+
+import sys
+from pathlib import Path
+sys.path.append(str(Path(__file__).parent.parent.parent / "core"))
+
+from database import VIMSDatabase
+
+
+def setup():
+    """Initialize database for satellite-validation."""
+    db = VIMSDatabase("satellite-validation")
+    db.create_schema(anomaly_classes=['resolution_mismatch', 'temporal_gap', 'cloud_obstruction', 'classification_error', 'change_undetected'])
+    print(f"Database initialized for Satellite vs Ground Truth")
+
+
+if __name__ == "__main__":
+    setup()

vims-core/instances/satellite-validation/src/detector.py

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+"""
+satellite-validation Anomaly Detector
+Generated by VIMS Instance Creator
+Related article: /insights/field-intelligence-vs-satellite/
+"""
+
+import sys
+from pathlib import Path
+sys.path.append(str(Path(__file__).parent.parent.parent / "core"))
+
+from base_detector import VIMSBaseDetector, VIMSInstanceRegistry
+
+
+class SatelliteValidationDetector(VIMSBaseDetector):
+    """
+    Anomaly detector for Satellite vs Ground Truth.
+    
+    Article: /insights/field-intelligence-vs-satellite/
+    """
+    
+    TOPIC = "satellite-validation"
+    CLASS_NAMES = {
+        0: "resolution_mismatch", 1: "temporal_gap", 2: "cloud_obstruction", 3: "classification_error", 4: "change_undetected"
+    }
+    
+    SEVERITY_MAP = {
+        "resolution_mismatch": 3, "temporal_gap": 3, "cloud_obstruction": 3, "classification_error": 3, "change_undetected": 3
+    }
+    
+    def preprocess(self, image):
+        """satellite-validation-specific preprocessing."""
+        # TODO: Implement specific preprocessing
+        return image
+    
+    def postprocess(self, raw_output):
+        """satellite-validation-specific postprocessing."""
+        # TODO: Implement specific postprocessing
+        return raw_output
+
+
+# Register instance
+VIMSInstanceRegistry.register("satellite-validation", SatelliteValidationDetector)