diff --git a/aws/lambda/benchmark_regression_summary_report/common/config.py b/aws/lambda/benchmark_regression_summary_report/common/config.py
index 6de12a84de..f37359e26f 100644
--- a/aws/lambda/benchmark_regression_summary_report/common/config.py
+++ b/aws/lambda/benchmark_regression_summary_report/common/config.py
@@ -11,6 +11,58 @@
 )
 
 
+PYTORCH_HELION_CONFIG = BenchmarkConfig(
+    name="Helion Benchmark Regression",
+    id="pytorch_helion",
+    source=BenchmarkApiSource(
+        api_query_url="https://hud.pytorch.org/api/benchmark/get_time_series",
+        type="benchmark_time_series_api",
+        api_endpoint_params_template="""
+                {
+                  "name": "pytorch_helion",
+                  "query_params": {
+                    "mode": "",
+                    "branches": ["main"],
+                    "repo": "pytorch/helion",
+                    "device": "",
+                    "arch":"",
+                    "benchmarkName": "Helion Benchmark",
+                    "startTime": "{{ startTime }}",
+                    "stopTime": "{{ stopTime }}"
+                    },
+                    "response_formats":["time_series"]
+                }
+                """,
+    ),
+    hud_info={
+        "url": "https://hud.pytorch.org/benchmark/v3/dashboard/pytorch_helion",
+    },
+    # set baseline from past 4-8 days, and compare with the lastest 4 day
+    policy=Policy(
+        frequency=Frequency(value=1, unit="days"),
+        range=RangeConfig(
+            baseline=DayRangeWindow(value=4),
+            comparison=DayRangeWindow(value=4),
+        ),
+        metrics={
+            "helion_speedup": RegressionPolicy(
+                name="helion_speedup",
+                condition="greater_equal",
+                threshold=0.85,
+                baseline_aggregation="median",
+            ),
+        },
+        notification_config={
+            "type": "github",
+            "repo": "pytorch/test-infra",
+            "issue": "7472",
+        },
+    ),
+    report_config=ReportConfig(
+        report_level="insufficient_data",
+    ),
+)
+
 PYTORCH_OPERATOR_MICROBENCH_CONFIG = BenchmarkConfig(
     name="Pytorch Operator Microbench Regression",
     id="pytorch_operator_microbenchmark",
@@ -146,6 +198,7 @@
     configs={
         "compiler_regression": COMPILER_BENCHMARK_CONFIG,
         "pytorch_operator_microbenchmark": PYTORCH_OPERATOR_MICROBENCH_CONFIG,
+        "pytorch_helion": PYTORCH_HELION_CONFIG,
     }
 )
 
diff --git a/aws/lambda/benchmark_regression_summary_report/common/regression_utils.py b/aws/lambda/benchmark_regression_summary_report/common/regression_utils.py
index 96c89ce61e..4ba306c2bf 100644
--- a/aws/lambda/benchmark_regression_summary_report/common/regression_utils.py
+++ b/aws/lambda/benchmark_regression_summary_report/common/regression_utils.py
@@ -77,16 +77,18 @@ class BenchmarkRegressionReport(TypedDict):
 
 
 def get_regression_status(regression_summary: BenchmarkRegressionSummary) -> str:
-    status = (
-        "regression"
-        if regression_summary.get("regression_count", 0) > 0
-        else (
-            "suspicious"
-            if regression_summary.get("suspicious_count", 0) > 0
-            else "no_regression"
-        )
-    )
-    return status
+    if regression_summary.get("regression_count", 0) > 0:
+        return "regression"
+    if regression_summary.get("suspicious_count", 0) > 0:
+        return "suspicious"
+    if regression_summary.get("insufficient_data_count", 0) > 0:
+        insufficient_data = regression_summary.get("insufficient_data_count", 0)
+        # default to 1 to avoid dividen issue
+        total = regression_summary.get("total_count", 1)
+        percentage = insufficient_data / total
+        if percentage >= 0.9:
+            return "insufficient_data"
+    return "no_regression"
 
 
 class BenchmarkRegressionReportGenerator:
@@ -251,7 +253,19 @@ def _to_data_map(
             for d in sorted(
                 ts_group.data, key=lambda d: isoparse(d["granularity_bucket"])
             ):
+                # skip if field is not in data, or field is None
                 if field not in d:
+                    logger.warning(
+                        "[_to_data_map] field %s not found or value is undefined", field
+                    )
+                    continue
+                if d[field] is None or math.isnan(float(d[field])):
+                    logger.warning(
+                        "[_to_data_map] Skip %s with value %s with group key [%s]",
+                        field,
+                        d[field],
+                        group_keys,
+                    )
                     continue
 
                 p: BenchmarkRegressionPoint = {
diff --git a/torchci/components/benchmark_v3/configs/configurations.tsx b/torchci/components/benchmark_v3/configs/configurations.tsx
index 6165ab21af..3935e31973 100644
--- a/torchci/components/benchmark_v3/configs/configurations.tsx
+++ b/torchci/components/benchmark_v3/configs/configurations.tsx
@@ -38,7 +38,7 @@ export const BENCHMARK_ID_MAPPING: Record<string, BenchmarkIdMappingItem> = {
  * @returns
  */
 export function getBenchmarkIdFromReportId(reportId: string): string {
-  return REPORT_ID_TO_BENCHMARK_ID_MAPPING[reportId] ?? "";
+  return REPORT_ID_TO_BENCHMARK_ID_MAPPING[reportId] ?? reportId;
 }
 
 export function getBenchmarkIdMappingItem(
diff --git a/torchci/components/benchmark_v3/pages/BenchmarkListPage.tsx b/torchci/components/benchmark_v3/pages/BenchmarkListPage.tsx
index d00a45c0ca..2eff527984 100644
--- a/torchci/components/benchmark_v3/pages/BenchmarkListPage.tsx
+++ b/torchci/components/benchmark_v3/pages/BenchmarkListPage.tsx
@@ -12,7 +12,8 @@ export function getBenchmarkMainRouteById(id: string): string | undefined {
       }
     }
   }
-  return undefined;
+  // by default, form the v3 route to dashboard page
+  return `/benchmark/v3/dashboard/${id}`;
 }
 
 export function benchmarkCategoryCardToNavGroup(