diff --git a/.github/workflows/base-run-bulk-upload.yml b/.github/workflows/base-run-bulk-upload.yml
index dfcc732ec..48c08af40 100644
--- a/.github/workflows/base-run-bulk-upload.yml
+++ b/.github/workflows/base-run-bulk-upload.yml
@@ -79,6 +79,13 @@ jobs:
             --empty-lloydgeorge-store
         working-directory: ./tests/bulk-upload/scripts
 
+      - name: Setup Document Review
+        run: |
+          python setup_document_review.py
+        working-directory: ./tests/bulk-upload/scripts
+        env:
+            ENVIRONMENT: "${{ inputs.sandbox }}"
+
       - name: Run Bulk Upload
         run: |
           python run_bulk_upload.py \
diff --git a/tests/bulk-upload/scripts/setup_document_review.py b/tests/bulk-upload/scripts/setup_document_review.py
new file mode 100644
index 000000000..c85872d42
--- /dev/null
+++ b/tests/bulk-upload/scripts/setup_document_review.py
@@ -0,0 +1,352 @@
+import csv
+import os
+import uuid
+from datetime import datetime, timedelta
+from typing import Any, Dict, List, NamedTuple
+
+import boto3
+from botocore.exceptions import ClientError
+
+SOURCE_PDF_FILE = "../source_to_copy_from.pdf"
+
+
+class Patient(NamedTuple):
+    full_name: str
+    date_of_birth: str
+    nhs_number: str
+    ods_code: str
+
+
+def get_timestamp(days_ago: int = 0) -> int:
+    target_date = datetime.now() - timedelta(days=days_ago)
+    return int(target_date.timestamp())
+
+
+def get_patients(filename: str) -> List[Dict]:
+    patients = []
+    csv_path = f"../test_patients_data/{filename}"
+
+    if not os.path.exists(csv_path):
+        print(f"Warning: {csv_path} not found.")
+
+    else:
+        with open(csv_path, mode="r", newline="") as file:
+            reader = csv.DictReader(file)
+            for idx, row in enumerate(reader):
+                if idx >= 300:
+                    break
+                patients.append(row)
+    return patients
+
+
+def parse_patient_record(raw_record: dict) -> Patient:
+    nhs_number = raw_record["NHS_NO"]
+    name_parts = [
+        raw_record["GIVEN_NAME"],
+        raw_record.get("OTHER_GIVEN_NAME", ""),
+        raw_record["FAMILY_NAME"],
+    ]
+    full_name = " ".join(name_part for name_part in name_parts if name_part)
+    date_of_birth = raw_record["DOB"].replace("/", "-")
+    ods_code = raw_record["GPP"]
+    return Patient(full_name, date_of_birth, nhs_number, ods_code)
+
+
+def build_document_review_object(
+    patient: Patient,
+    review_id: str,
+    files: List[Dict[str, str]],
+    review_status: str = "PENDING_REVIEW",
+    review_reason: str = "General error",
+    days_ago_uploaded: int = 1,
+    reviewer: str | None = None,
+    review_date: int | None = None,
+    document_reference_id: str | None = None,
+) -> Dict[str, Any]:
+    upload_timestamp = int(get_timestamp(days_ago=days_ago_uploaded))
+
+    review_obj = {
+        "ID": review_id,
+        "Version": 1,
+        "Author": f"{patient.ods_code}",
+        "Custodian": patient.ods_code,
+        "ReviewStatus": review_status,
+        "ReviewReason": review_reason,
+        "UploadDate": upload_timestamp,
+        "Files": files,
+        "NhsNumber": patient.nhs_number,
+        "DocumentSnomedCodeType": "16521000000101",  # Lloyd George code
+    }
+
+    if reviewer:
+        review_obj["Reviewer"] = reviewer
+
+    if review_date:
+        review_obj["ReviewDate"] = review_date
+
+    if document_reference_id:
+        review_obj["DocumentReferenceId"] = document_reference_id
+
+    return review_obj
+
+
+def build_file_reference(
+    upload_id, file_name: str, bucket_name: str
+) -> Dict[str, str]:
+    s3_key = f"{upload_id}/{file_name}"
+    file_location = f"s3://{bucket_name}/{s3_key}"
+
+    return {
+        "FileName": file_name,
+        "FileLocation": file_location,
+    }
+
+
+def create_test_scenarios(patients: List[Patient], bucket_name: str):
+
+    review_objects = []
+    files_to_upload = []
+
+    def scenario_1(patient):
+        """Pending Review with single file"""
+        file_name = f"upload_review_{patient.nhs_number}_doc1.pdf"
+        review_id = str(uuid.uuid4())
+        files = [build_file_reference(review_id, file_name, bucket_name)]
+        review_obj = build_document_review_object(
+            review_id=review_id,
+            patient=patient,
+            files=files,
+            review_status="PENDING_REVIEW",
+            review_reason="General error",
+            days_ago_uploaded=1,
+        )
+        return review_obj, [(patient.nhs_number, file_name, files[0]["FileLocation"])]
+
+    def scenario_2(patient):
+        """Pending Review with multiple files"""
+
+        files = []
+        files_list = []
+        review_id = str(uuid.uuid4())
+
+        for i in range(3):
+            file_name = f"upload_review_{patient.nhs_number}_doc{i+1}.pdf"
+            file_ref = build_file_reference(review_id, file_name, bucket_name)
+            files.append(file_ref)
+            files_list.append((patient.nhs_number, file_name, file_ref["FileLocation"]))
+        review_obj = build_document_review_object(
+            review_id=review_id,
+            patient=patient,
+            files=files,
+            review_status="PENDING_REVIEW",
+            review_reason="More or less files than we expected",
+            days_ago_uploaded=2,
+        )
+        return review_obj, files_list
+
+    def scenario_3(patient):
+        """Approved review"""
+        file_name = f"upload_review_{patient.nhs_number}_doc1.pdf"
+        review_id = str(uuid.uuid4())
+        files = [build_file_reference(review_id, file_name, bucket_name)]
+        review_obj = build_document_review_object(
+            patient=patient,
+            review_id=review_id,
+            files=files,
+            review_status="APPROVED",
+            review_reason="Demographic mismatches",
+            days_ago_uploaded=5,
+            reviewer="H81109",
+            review_date=get_timestamp(days_ago=2),
+            document_reference_id=str(uuid.uuid4()),
+        )
+        return review_obj, [(patient.nhs_number, file_name, files[0]["FileLocation"])]
+
+    def scenario_4(patient):
+        """Rejected review"""
+        file_name = f"upload_review_{patient.nhs_number}_doc1.pdf"
+        review_id = str(uuid.uuid4())
+        files = [build_file_reference(review_id, file_name, bucket_name)]
+        review_obj = build_document_review_object(
+            review_id=review_id,
+            patient=patient,
+            files=files,
+            review_status="REJECTED",
+            review_reason="Filename Naming convention error",
+            days_ago_uploaded=7,
+            reviewer="H81109",
+            review_date=get_timestamp(days_ago=3),
+        )
+        return review_obj, [(patient.nhs_number, file_name, files[0]["FileLocation"])]
+
+    def scenario_5(patient):
+        """Approved with multiple files and document reference"""
+
+        files = []
+        files_list = []
+        review_id = str(uuid.uuid4())
+
+        for i in range(2):
+            file_name = f"upload_review_{patient.nhs_number}_doc{i+1}.pdf"
+            file_ref = build_file_reference(review_id, file_name, bucket_name)
+            files.append(file_ref)
+            files_list.append((patient.nhs_number, file_name, file_ref["FileLocation"]))
+
+        review_obj = build_document_review_object(
+            review_id=review_id,
+            patient=patient,
+            files=files,
+            review_status="APPROVED",
+            review_reason="Duplicate records error",
+            days_ago_uploaded=10,
+            reviewer="H81109",
+            review_date=get_timestamp(days_ago=5),
+            document_reference_id=str(uuid.uuid4()),
+        )
+        return review_obj, files_list
+
+
+    def scenario_6(patient):
+        """random document type review"""
+
+        file_name = f"random_upload_{patient.nhs_number}.txt"
+        review_id = str(uuid.uuid4())
+        files = [build_file_reference(review_id, file_name, bucket_name)]
+        review_obj = build_document_review_object(
+            review_id=review_id,
+            patient=patient,
+            files=files,
+            review_status="PENDING_REVIEW",
+            review_reason="Unknown NHS number",
+            days_ago_uploaded=3,
+        )
+        review_obj["DocumentSnomedCodeType"] = "734163000"
+        return review_obj, [(patient.nhs_number, file_name, files[0]["FileLocation"])]
+
+    def scenario_7(patient):
+        """Multiple versions: NEVER_REVIEWED (v1) and PENDING_REVIEW (v2) with different custodians"""
+
+        review_id = str(uuid.uuid4())
+        file_name = f"upload_review_{patient.nhs_number}_doc1.pdf"
+
+        files = [build_file_reference(review_id, file_name, bucket_name)]
+
+        review_obj_v1 = build_document_review_object(
+            review_id=review_id,
+            patient=patient,
+            files=files,
+            review_status="NEVER_REVIEWED",
+            review_reason="General error",
+            review_date=get_timestamp(days_ago=1),
+            days_ago_uploaded=15,
+        )
+        review_obj_v1["Version"] = 1
+        review_obj_v1["Author"] = "A12345"
+        review_obj_v1["Reviewer"] = "A12345"
+
+        review_obj_v2 = build_document_review_object(
+            review_id=review_id,
+            patient=patient,
+            files=files,
+            review_status="PENDING_REVIEW",
+            review_reason="General error",
+            days_ago_uploaded=15,
+        )
+        review_obj_v2["Version"] = 2
+        review_obj_v1["Author"] = "A12345"
+        review_obj_v2["Custodian"] = "H81109"
+
+        files_list = [
+            (patient.nhs_number, file_name, files[0]["FileLocation"])
+        ]
+
+        return [review_obj_v1, review_obj_v2], files_list
+
+    scenarios = [
+        scenario_1,
+        scenario_2,
+        scenario_3,
+        scenario_4,
+        scenario_5,
+        scenario_6,
+        scenario_7,
+    ]
+
+    for idx, patient in enumerate(patients):
+        scenario_func = scenarios[idx % len(scenarios)]
+        result = scenario_func(patient)
+        review_obj, patient_files = result
+
+        if isinstance(review_obj, list):
+            review_objects.extend(review_obj)
+        else:
+            review_objects.append(review_obj)
+
+        files_to_upload.extend(patient_files)
+
+    return review_objects, files_to_upload
+
+
+def upload_files_to_s3(files_to_upload: List[tuple], source_pdf: str):
+    s3_client = boto3.client("s3")
+
+    for nhs_number, file_name, file_location in files_to_upload:
+        s3_location = file_location.replace("s3://", "")
+        bucket_name, s3_key = s3_location.split("/", 1)
+
+        try:
+            s3_client.upload_file(
+                Filename=source_pdf,
+                Bucket=bucket_name,
+                Key=s3_key,
+                ExtraArgs={"ContentType": "application/pdf"},
+            )
+        except FileNotFoundError:
+            print(f"Source file not found: {source_pdf}")
+        except ClientError as e:
+            print(f"Error uploading {file_name}: {e}")
+
+
+def write_to_dynamodb(review_objects: List[Dict[str, Any]], table_name: str):
+    dynamodb = boto3.resource("dynamodb")
+    table = dynamodb.Table(table_name)
+
+    try:
+        with table.batch_writer() as batch:
+            for review_obj in review_objects:
+                batch.put_item(Item=review_obj)
+        print(f"\nSuccessfully wrote {len(review_objects)} review objects to DynamoDB")
+    except ClientError as e:
+        print(f"Error writing to DynamoDB: {e.response['Error']['Message']}")
+        raise
+
+
+def main():
+    environment = os.environ.get("ENVIRONMENT", "ndr-dev")
+    bucket_name = f"{environment}-document-pending-review-store"
+    table_name = f"{environment}_DocumentUploadReview"
+    patient_file = os.environ.get("PATIENT_DATA_FILE", "ODS_Code_H81109.csv")
+
+    try:
+        patients_data = get_patients(patient_file)
+        patients = [parse_patient_record(record) for record in patients_data]
+        print(f"Loaded {len(patients)} patients")
+    except Exception as e:
+        print(f"Error loading patients: {e}")
+        return
+
+    review_objects, files_to_upload = create_test_scenarios(patients, bucket_name)
+    print(f"Created {len(review_objects)} review objects with {len(files_to_upload)} files")
+
+    print("\nUploading files to S3...")
+    upload_files_to_s3(files_to_upload, SOURCE_PDF_FILE)
+
+    print("\nWriting to DynamoDB...")
+    write_to_dynamodb(review_objects, table_name)
+
+    print("SETUP COMPLETE")
+
+
+if __name__ == "__main__":
+    main()
+