M3: implement Data Quality Workbench

Five rule scanners (duplicate customers, missing fields, odometer regression, booking overlap, status conflict) run automatically after seed and via an explicit scan endpoint. Issue defer/reject/merge-customers endpoints with transactional customer merge (booking rewiring, tombstone, audit). Data Quality nav + workbench UI with two-column duplicate comparison and inline (non-native) confirm. Dashboard attention items now link to issues. 35 backend tests passing, ruff clean. Fixed a real false-positive bug in odometer-regression detection found through iteration on seed data, and two TS narrowing errors. Verified end-to-end via browser: S2 merge and S4 overlap scenarios.

backend/app/main.py

@@ -4,7 +4,7 @@ from fastapi import FastAPI, HTTPException, Request
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import JSONResponse
 
-from app.api.routers import audit, bookings, dashboard, demo, vehicles
+from app.api.routers import audit, bookings, dashboard, data_quality, demo, vehicles
 from app.core.config import get_settings
 from app.core.errors import AppError, error_body
 
@@ -61,3 +61,4 @@ app.include_router(dashboard.router)
 app.include_router(vehicles.router)
 app.include_router(bookings.router)
 app.include_router(audit.router)
+app.include_router(data_quality.router)