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/sidewalk-accessibility/README.md

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+# Sidewalk Accessibility Audit
+
+VIMS instance for sidewalk-accessibility.
+
+## Related Article
+[/insights/how-to-measure-urban-decay/](https://landvex.com/insights/how-to-measure-urban-decay/)
+
+## Anomaly Classes
+- cracked_surface
+- missing_curb_ramp
+- obstruction
+- uneven_surface
+- narrow_path
+
+## 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/sidewalk-accessibility/predict`
+- WebSocket: `ws://host/ws/sidewalk-accessibility/alerts`

vims-core/instances/sidewalk-accessibility/config.yaml

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+# sidewalk-accessibility configuration
+
+topic: sidewalk-accessibility
+display_name: Sidewalk Accessibility Audit
+article_url: /insights/how-to-measure-urban-decay/
+
+anomaly_classes:
+  - cracked_surface
+  - missing_curb_ramp
+  - obstruction
+  - uneven_surface
+  - narrow_path
+
+model:
+  base: yolov8n.pt
+  input_size: 640
+  
+training:
+  epochs: 100
+  batch_size: 16

vims-core/instances/sidewalk-accessibility/src/database.py

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+"""
+Database setup for Sidewalk Accessibility Audit
+"""
+
+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 sidewalk-accessibility."""
+    db = VIMSDatabase("sidewalk-accessibility")
+    db.create_schema(anomaly_classes=['cracked_surface', 'missing_curb_ramp', 'obstruction', 'uneven_surface', 'narrow_path'])
+    print(f"Database initialized for Sidewalk Accessibility Audit")
+
+
+if __name__ == "__main__":
+    setup()

vims-core/instances/sidewalk-accessibility/src/detector.py

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+"""
+sidewalk-accessibility Anomaly Detector
+Generated by VIMS Instance Creator
+Related article: /insights/how-to-measure-urban-decay/
+"""
+
+import sys
+from pathlib import Path
+sys.path.append(str(Path(__file__).parent.parent.parent / "core"))
+
+from base_detector import VIMSBaseDetector, VIMSInstanceRegistry
+
+
+class SidewalkAccessibilityDetector(VIMSBaseDetector):
+    """
+    Anomaly detector for Sidewalk Accessibility Audit.
+    
+    Article: /insights/how-to-measure-urban-decay/
+    """
+    
+    TOPIC = "sidewalk-accessibility"
+    CLASS_NAMES = {
+        0: "cracked_surface", 1: "missing_curb_ramp", 2: "obstruction", 3: "uneven_surface", 4: "narrow_path"
+    }
+    
+    SEVERITY_MAP = {
+        "cracked_surface": 3, "missing_curb_ramp": 3, "obstruction": 3, "uneven_surface": 3, "narrow_path": 3
+    }
+    
+    def preprocess(self, image):
+        """sidewalk-accessibility-specific preprocessing."""
+        # TODO: Implement specific preprocessing
+        return image
+    
+    def postprocess(self, raw_output):
+        """sidewalk-accessibility-specific postprocessing."""
+        # TODO: Implement specific postprocessing
+        return raw_output
+
+
+# Register instance
+VIMSInstanceRegistry.register("sidewalk-accessibility", SidewalkAccessibilityDetector)