diff --git a/backend/engine/engine.py b/backend/engine/engine.py
index e24a3b95..f7a374e0 100644
--- a/backend/engine/engine.py
+++ b/backend/engine/engine.py
@@ -652,7 +652,8 @@ async def model_engine(body: PlanTriggerRequest):
                 epc_records["original_epc"]["estimated"] = False
 
             prepared_epc = EPCRecord(
-                epc_records=epc_records, run_mode="newdata", cleaning_data=cleaning_data, address_metadata=addr
+                epc_records=epc_records, run_mode="newdata", cleaning_data=cleaning_data,
+                # address_metadata=addr  Switched off to remove injecting landlord inputs
             )
 
             input_properties.append(
diff --git a/etl/epc/Record.py b/etl/epc/Record.py
index defe13f4..8dbb5ba5 100644
--- a/etl/epc/Record.py
+++ b/etl/epc/Record.py
@@ -580,7 +580,22 @@ class EPCRecord:
                 if existing is not None and v is not None and abs(existing - v) > 1:  # 1m tolerance
                     self.landlord_differences[k] = v
             else:
-                if v != self._prepared_epc.get(k) and (not pd.isnull(v)) and (not pd.isnull(self._prepared_epc.get(k))):
+
+                # Check if something has been cleaned. We want to avoid triggering re-baselining if we cleaned
+                # a value. In the address meta, it will possibly contain the original value, so we'd pick up a
+                # diference if the original value was something to be cleaned, we clean that value and then end up
+                # comparing the original value to the new clean one
+                cleaned_value = self._prepared_epc.get(k)
+                original_value = self.original_epc.get(k.replace("_", "-"))
+
+                # We check if the value has been cleaned
+                if cleaned_value != original_value:
+                    # The thing we want to compare against, is the original value
+                    compare_to = original_value
+                else:
+                    compare_to = cleaned_value
+
+                if v != compare_to and (not pd.isnull(v)) and (not pd.isnull(self._prepared_epc.get(k))):
                     self.landlord_differences[k] = v
 
         self._prepared_epc.update(self.landlord_differences)