diff --git a/.env.example b/.env.example
index dfc7703..b3948ba 100644
--- a/.env.example
+++ b/.env.example
@@ -1,5 +1,8 @@
-BACKEND_PORT=8000
-CORS_ORIGINS=http://localhost:5173,http://localhost
+BACKEND_PORT=8060
+CORS_ORIGINS=http://localhost:5173,http://localhost:8061
 DATABASE_URL=sqlite:////data/jardin.db
 UPLOAD_DIR=/data/uploads
-VITE_API_URL=http://localhost:8000
+VITE_API_URL=http://localhost:8060
+PLANTNET_API_KEY=2b1088cHCJ4c7Cn2Vqq67xfve
+AI_SERVICE_URL=http://ai-service:8070
+REDIS_URL=redis://redis:6379
diff --git a/backend/app/services/plantnet.py b/backend/app/services/plantnet.py
new file mode 100644
index 0000000..1a3edf1
--- /dev/null
+++ b/backend/app/services/plantnet.py
@@ -0,0 +1,35 @@
+import os
+from typing import List
+
+import httpx
+
+PLANTNET_KEY = os.environ.get("PLANTNET_API_KEY", "2b1088cHCJ4c7Cn2Vqq67xfve")
+PLANTNET_URL = "https://my-api.plantnet.org/v2/identify/all"
+
+
+async def identify(image_bytes: bytes, filename: str = "photo.jpg") -> List[dict]:
+    """Appelle PlantNet et retourne les 3 meilleures identifications."""
+    try:
+        async with httpx.AsyncClient(timeout=10.0) as client:
+            resp = await client.post(
+                PLANTNET_URL,
+                params={"api-key": PLANTNET_KEY, "nb-results": 3},
+                files={"images": (filename, image_bytes, "image/jpeg")},
+                data={"organs": ["auto"]},
+            )
+            resp.raise_for_status()
+            data = resp.json()
+    except Exception:
+        return []
+
+    results = []
+    for r in data.get("results", [])[:3]:
+        species = r.get("species", {})
+        common_names = species.get("commonNames", [])
+        results.append({
+            "species": species.get("scientificNameWithoutAuthor", ""),
+            "common_name": common_names[0] if common_names else "",
+            "confidence": round(r.get("score", 0.0), 3),
+            "image_url": (r.get("images", [{}]) or [{}])[0].get("url", {}).get("m", ""),
+        })
+    return results
diff --git a/backend/app/services/yolo_service.py b/backend/app/services/yolo_service.py
new file mode 100644
index 0000000..f0164e0
--- /dev/null
+++ b/backend/app/services/yolo_service.py
@@ -0,0 +1,45 @@
+import os
+from typing import List
+
+import httpx
+
+AI_SERVICE_URL = os.environ.get("AI_SERVICE_URL", "http://localhost:8070")
+
+# Mapping class_name YOLO → nom commun français (partiel)
+_NOMS_FR = {
+    "Tomato___healthy": "Tomate (saine)",
+    "Tomato___Early_blight": "Tomate (mildiou précoce)",
+    "Tomato___Late_blight": "Tomate (mildiou tardif)",
+    "Pepper__bell___healthy": "Poivron (sain)",
+    "Apple___healthy": "Pommier (sain)",
+    "Potato___healthy": "Pomme de terre (saine)",
+    "Grape___healthy": "Vigne (saine)",
+    "Corn_(maize)___healthy": "Maïs (sain)",
+    "Strawberry___healthy": "Fraisier (sain)",
+    "Peach___healthy": "Pêcher (sain)",
+}
+
+
+async def identify(image_bytes: bytes) -> List[dict]:
+    """Appelle l'ai-service interne et retourne les détections YOLO."""
+    try:
+        async with httpx.AsyncClient(timeout=30.0) as client:
+            resp = await client.post(
+                f"{AI_SERVICE_URL}/detect",
+                files={"file": ("photo.jpg", image_bytes, "image/jpeg")},
+            )
+            resp.raise_for_status()
+            data = resp.json()
+    except Exception:
+        return []
+
+    results = []
+    for det in data[:3]:
+        cls = det.get("class_name", "")
+        results.append({
+            "species": cls.replace("___", " — ").replace("_", " "),
+            "common_name": _NOMS_FR.get(cls, cls.split("___")[0].replace("_", " ")),
+            "confidence": det.get("confidence", 0.0),
+            "image_url": "",
+        })
+    return results