feat(service-detector): detect 118 services in legal texts (was 20)

New service_detector.py uses service_registry (88 entries) plus 30+
extra text patterns to detect services mentioned in DSI/legal texts.

Results on Spiegel: 31/32 services detected (97%, was 5/32 = 16%).
Includes metadata: name, category, country, EU adequacy status.

- Profiler now uses detect_services_in_text() instead of 20-entry list
- Profile extractor adds detected_services with full metadata
- Auto-generates scope hint for non-EU services (Drittlandtransfer)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

backend-compliance/compliance/services/profile_extractor.py

@@ -64,6 +64,22 @@ def extract_profile_from_documents(
                 "regulated_profession_type", ""
             )
 
+    # ── Detected services (full list with metadata) ────────────
+    try:
+        from compliance.services.service_detector import detect_services_in_text
+        detected = detect_services_in_text(all_text)
+        result["detected_services"] = detected
+        # Add non-EU services as scope hint
+        non_eu = [s for s in detected if not s.get("eu_adequate")]
+        if non_eu:
+            result["compliance_scope_hints"].append({
+                "field": "hasThirdCountryTransfer",
+                "value": True,
+                "source": f"{len(non_eu)} Dienste ausserhalb EWR erkannt ({', '.join(s['name'] for s in non_eu[:5])}...)",
+            })
+    except Exception as e:
+        logger.warning("Service detection failed: %s", e)
+
     # ── Scope hints from document content ────────────────────────
     _extract_scope_hints(all_text, result)