diff --git a/skyvern/forge/sdk/services/observer_service.py b/skyvern/forge/sdk/services/observer_service.py
index d94e25e9..3718a629 100644
--- a/skyvern/forge/sdk/services/observer_service.py
+++ b/skyvern/forge/sdk/services/observer_service.py
@@ -394,6 +394,7 @@ async def run_observer_cruise_helper(
             break
 
         block: BlockTypeVar | None = None
+        task_history_record: dict[str, Any] = {}
         if task_type == "extract":
             block, block_yaml_list, parameter_yaml_list = await _generate_extraction_task(
                 observer_cruise=observer_cruise,
@@ -405,7 +406,7 @@ async def run_observer_cruise_helper(
                 data_extraction_goal=plan,
                 task_history=task_history,
             )
-            task_history.append({"type": task_type, "task": plan})
+            task_history_record = {"type": task_type, "task": plan}
         elif task_type == "navigate":
             original_url = url if i == 0 else None
             block, block_yaml_list, parameter_yaml_list = await _generate_navigation_task(
@@ -415,7 +416,7 @@ async def run_observer_cruise_helper(
                 original_url=original_url,
                 navigation_goal=plan,
             )
-            task_history.append({"type": task_type, "task": plan})
+            task_history_record = {"type": task_type, "task": plan}
         elif task_type == "loop":
             try:
                 block, block_yaml_list, parameter_yaml_list, extraction_obj, inner_task = await _generate_loop_task(
@@ -428,14 +429,12 @@ async def run_observer_cruise_helper(
                     original_url=url,
                     scraped_page=scraped_page,
                 )
-                task_history.append(
-                    {
-                        "type": task_type,
-                        "task": plan,
-                        "loop_over_values": extraction_obj.loop_values,
-                        "task_inside_the_loop": inner_task,
-                    }
-                )
+                task_history_record = {
+                    "type": task_type,
+                    "task": plan,
+                    "loop_over_values": extraction_obj.loop_values,
+                    "task_inside_the_loop": inner_task,
+                }
             except Exception:
                 LOG.exception("Failed to generate loop task")
                 await app.WORKFLOW_SERVICE.mark_workflow_run_as_failed(
@@ -453,6 +452,15 @@ async def run_observer_cruise_helper(
         # generate the extraction task
         block_result = await block.execute_safe(workflow_run_id=workflow_run_id, organization_id=organization_id)
 
+        extracted_data = _get_extracted_data_from_block_result(
+            block_result,
+            task_type,
+            observer_cruise_id=observer_cruise_id,
+            workflow_run_id=workflow_run_id,
+        )
+        if extracted_data is not None:
+            task_history_record["extracted_data"] = extracted_data
+        task_history.append(task_history_record)
         # refresh workflow
         yaml_blocks.extend(block_yaml_list)
         yaml_parameters.extend(parameter_yaml_list)
@@ -1018,3 +1026,62 @@ async def mark_observer_cruise_as_failed(
         await app.WORKFLOW_SERVICE.mark_workflow_run_as_failed(
             workflow_run_id, failure_reason=failure_reason or "Observer cruise failed"
         )
+
+
+def _get_extracted_data_from_block_result(
+    block_result: BlockResult,
+    task_type: str,
+    observer_cruise_id: str | None = None,
+    workflow_run_id: str | None = None,
+) -> Any | None:
+    """Extract data from block result based on task type.
+
+    Args:
+        block_result: The result from block execution
+        task_type: Type of task ("extract" or "loop")
+        observer_cruise_id: Optional ID for logging
+        workflow_run_id: Optional ID for logging
+
+    Returns:
+        Extracted data if available, None otherwise
+    """
+    if task_type == "extract":
+        if (
+            isinstance(block_result.output_parameter_value, dict)
+            and "extracted_information" in block_result.output_parameter_value
+            and block_result.output_parameter_value["extracted_information"]
+        ):
+            return block_result.output_parameter_value["extracted_information"]
+    elif task_type == "loop":
+        # if loop task has data extraction, add it to the task history
+        # WARNING: the assumption here is that the output_paremeter_value is a list of list of dicts
+        #          output_parameter_value data structure is not consistent across all the blocks
+        if block_result.output_parameter_value and isinstance(block_result.output_parameter_value, list):
+            loop_output_overall = []
+            for inner_loop_output in block_result.output_parameter_value:
+                inner_loop_output_overall = []
+                if not isinstance(inner_loop_output, list):
+                    LOG.warning(
+                        "Inner loop output is not a list",
+                        inner_loop_output=inner_loop_output,
+                        observer_cruise_id=observer_cruise_id,
+                        workflow_run_id=workflow_run_id,
+                        workflow_run_block_id=block_result.workflow_run_block_id,
+                    )
+                    continue
+                for inner_output in inner_loop_output:
+                    if not isinstance(inner_output, dict):
+                        LOG.warning(
+                            "inner output is not a dict",
+                            inner_output=inner_output,
+                            observer_cruise_id=observer_cruise_id,
+                            workflow_run_id=workflow_run_id,
+                            workflow_run_block_id=block_result.workflow_run_block_id,
+                        )
+                        continue
+                    output_value = inner_output.get("output_value", {})
+                    if "extracted_information" in output_value and output_value["extracted_information"]:
+                        inner_loop_output_overall.append(output_value["extracted_information"])
+                loop_output_overall.append(inner_loop_output_overall)
+            return loop_output_overall if loop_output_overall else None
+    return None