diff --git a/backend/engine/engine.py b/backend/engine/engine.py
index 2427ca8a..8410024d 100644
--- a/backend/engine/engine.py
+++ b/backend/engine/engine.py
@@ -405,6 +405,29 @@ def check_duplicate_uprns(plan_input):
     return True
 
 
+def check_duplicate_property_ids(input_properties):
+    """
+    Simple function to check if the input data contains duplicated property IDs. This will happen in very rare
+    cases where we have properties across different servers, where the input UPRN is possibly incorrect and we
+    find the right property via an address search, instead of a UPRN search and so we end up with the same property
+    twice.
+    :param input_properties:
+    :return:
+    """
+
+    input_property_ids = [x.id for x in input_properties]
+
+    if input_property_ids:
+        # Check for dupes
+        if len(input_property_ids) != len(set(input_property_ids)):
+            # Find the duplicate property IDs
+            duplicates = set([x for x in input_property_ids if input_property_ids.count(x) > 1])
+            # de-dupe input_uprns
+            raise ValueError(f"Duplicate property IDs in the input data: {duplicates}")
+
+    return True
+
+
 def averages_cleaning(prepared_epc: EPCRecord, cleaning_data: pd.DataFrame):
     """
     Placeholder cleaning function to handle edge cases where we have missing data for
@@ -780,6 +803,8 @@ async def model_engine(body: PlanTriggerRequest):
         if not input_properties:
             return Response(status_code=204)
 
+        check_duplicate_property_ids(input_properties)
+
         # We check if we have inspections data and store it in the database if so. We'll update or create
         # aginst each property if
         if inspections_map:
diff --git a/recommendations/WindowsRecommendations.py b/recommendations/WindowsRecommendations.py
index bc5e6066..a5561d20 100644
--- a/recommendations/WindowsRecommendations.py
+++ b/recommendations/WindowsRecommendations.py
@@ -190,7 +190,7 @@ class WindowsRecommendations:
             raise ValueError("Invalid glazing type - implement me")
 
         if self.property.data["windows-energy-eff"] == "Very Good":
-            raise ValueError("Very Good energy efficiency is not supported")
+            windows_energy_eff = "Very Good"
 
         # For post 2002 windows, the energy efficiency is "Good" and so for the simulation, we simulate with "Good"