diff --git a/src/prsv_tools/report/create_ingest_report.py b/src/prsv_tools/report/create_ingest_report.py
new file mode 100644
index 0000000..c705aa7
--- /dev/null
+++ b/src/prsv_tools/report/create_ingest_report.py
@@ -0,0 +1,114 @@
+import argparse
+import re
+from pathlib import Path
+from datetime import datetime
+
+import pandas as pd
+
+
+def _make_parser():
+    parser = argparse.ArgumentParser(
+        description="""Generate an ingest report.
+                       Require a folder with Excel files from
+                       Preservica's unpack script
+                       And require a file name"""
+    )
+    parser.add_argument(
+        "--folder",
+        "-f",
+        type=str,
+        required=True,
+        help="a folder with Excel files",
+    )
+    parser.add_argument(
+        "--filename",
+        "-fn",
+        type=str,
+        required=True,
+        help="file name for the csv file",
+    )
+
+    return parser
+
+
+def combine_excel(folder: Path):
+    """Combine all the XLSX files in designated folder together into
+    a data frame"""
+    file_ls = [
+        x
+        for x in folder.iterdir()
+        if x.is_file()
+        and x.suffix.lower() == ".xlsx"
+        and not x.name.startswith(".")
+        and not x.name.startswith("~$")
+    ]
+    print(file_ls)
+    df = pd.DataFrame()
+    for excel in file_ls:
+        df_new = pd.read_excel(excel, index_col=0)
+        df = pd.concat([df, df_new])
+
+    return df
+
+
+def determine_io_type(file_name):
+    """Using regular expression of the file name to determine whether it is a
+    metadata or asset file"""
+    if re.search(r"^M\d+_(EM|DI|ER)_\d+", file_name):
+        return "Metadata"
+    else:
+        return "Asset"
+
+
+def determine_ingest_month(ingest_date):
+    """Extract year-month information from the IngestDate column"""
+    dt_obj = datetime.fromisoformat(ingest_date)
+    year_month_str = f"{dt_obj.year}-{dt_obj.strftime('%m')}"
+
+    return year_month_str
+
+
+def add_columns(df):
+    """Add IO Type column and Object Type column"""
+    df["IO Type"] = df["File Name"].apply(determine_io_type)
+    df["Object Type"] = "DigArch"
+    df["Ingest Month"] = df["IngestDate"].apply(determine_ingest_month)
+
+    return df
+
+
+def get_summary_info(df):
+    """Get summary information with specific columns"""
+    summary_info = (
+        df.groupby(["Ingest Month", "Object Type", "IO Type"])
+        .agg({"File Size": "sum", "File Name": "count"})
+        .reset_index()
+    )
+    summary_info.columns = [
+        "Ingest Month",
+        "Object Type",
+        "IO Type",
+        "Total File Size",
+        "Number of Files",
+    ]
+
+    return summary_info
+
+
+def main():
+    parser = _make_parser()
+    args = parser.parse_args()
+
+    folder_path = Path(args.folder)
+    file_name = args.filename
+    combined_df = combine_excel(folder_path)
+
+    extract_df = add_columns(combined_df)
+
+    summary_info = get_summary_info(extract_df)
+
+    summary_info.to_csv(f"{file_name}.csv", index=False)
+
+
+if __name__ == "__main__":
+    main()