diff --git a/etl/eligibility/ha_15_32/ha_analysis_batch_3.py b/etl/eligibility/ha_15_32/ha_analysis_batch_3.py
index 53ce69e2..9462642f 100644
--- a/etl/eligibility/ha_15_32/ha_analysis_batch_3.py
+++ b/etl/eligibility/ha_15_32/ha_analysis_batch_3.py
@@ -5119,7 +5119,9 @@ def forecast_remaining_sales(loader):
 
 
 def fml_data_pull(loader):
-    has_bruh = ["HA7", "HA14", "HA25", "HA39", "HA16"]
+    has_bruh = ["HA7", "HA14", "HA25", "HA39", "HA16",
+                # Do these
+                "HA1", "HA13", "HA50", "HA24"]
     # DO
     from backend.SearchEpc import SearchEpc
     epc_api_key = "a2Nvbm5rb3dsZXNzYXJAZ21haWwuY29tOjY5MGJiMWM0NmIyOGI5ZDUxYzAxMzQzYzNiZGNlZGJjZDNmODQwMzA="
@@ -5197,9 +5199,19 @@ def fml_analysis(loader):
     no_ciga_cavity_descriptions = [
         "Cavity wall, as built, insulated (assumed)",
         "Cavity wall, as built, no insulation (assumed)",
-        "Cavity wall, as built, partial insulation (assumed)"
+        "Cavity wall, as built, partial insulation (assumed)",
+        "Cavity wall, no insulation (assumed)",
+        "Cavity wall, partial insulation (assumed)",
+        "Cavity wall,",
+        "Cavity wall, insulated (assumed)",
+        "Cavity wall, no insulation (assumed)",
+        "Cavity wall, as built, insulated (assumed)",
+        "Cavity wall, partial insulation (assumed)",
     ]
 
+    # TODO: There will be some properties that are subject to CIGA that do not look like they ned a CIGA check! pass
+    #  them!
+
     codes = [
         "HA39", "HA14", "HA24", "HA15", "HA32", "HA28", "HA6", "HA1", "HA7",
         "HA16", "HA107", "HA25", "HA50", "HA41", "HA48", "HA2", "HA63", "HA12",
@@ -5217,6 +5229,7 @@ def fml_analysis(loader):
     remaining_eligible_mapping = dict(zip(codes, values))
 
     results = []
+    wall_descriptions = []
     for ha_name in has_bruh:
 
         original_figures = loader.december_figures[
@@ -5236,6 +5249,7 @@ def fml_analysis(loader):
         # We make sure we don't have duplicated. We do a super basic drop duplicates because it shouldn't be a huge
         # issue at this point
         epc_data = epc_data.drop_duplicates("uprn")
+        wall_descriptions.extend(epc_data["walls-description"].unique().tolist())
 
         # time from the inspection to now
         epc_data["epc_age"] = (datetime.now() - pd.to_datetime(epc_data["inspection-date"])).dt.days
@@ -5464,6 +5478,10 @@ def fml_analysis(loader):
 
     results_df = pd.DataFrame(results)
 
+    wall_descriptions = list(set(wall_descriptions))
+    from pprint import pprint
+    pprint(wall_descriptions)
+
     # results_df["Delta vs November"] = 100 * (
     #     results_df["Of which ECO4 Eligible - Remaining"] - results_df["Original ECO4 Estimate - Remaining"]
     # ) / results_df["Original ECO4 Estimate - Remaining"]
diff --git a/etl/epc_clean/app.py b/etl/epc_clean/app.py
index 53c1a329..3f1a1a80 100644
--- a/etl/epc_clean/app.py
+++ b/etl/epc_clean/app.py
@@ -36,8 +36,11 @@ def app():
     cleaned_data = {}
     epc_directories = [entry for entry in EPC_DIRECTORY.iterdir() if entry.is_dir()]
 
+    WALLS = []
     for directory in tqdm(epc_directories):
         data = pd.read_csv(directory / "certificates.csv", low_memory=False)
+        z = data["WALLS_DESCRIPTION"].unique().tolist()
+        WALLS.extend(z)
         # Rename the columns to the same format as the api returns
         data.columns = [c.replace("_", "-").lower() for c in data.columns]
         # Take just date before the date threshold