diff --git a/src/models/processors.py b/src/models/processors.py
index f73f53bce..2cabb1fa5 100644
--- a/src/models/processors.py
+++ b/src/models/processors.py
@@ -560,10 +560,16 @@ async def process_item(self, upload_task: UploadTask, item: str, file_task: File
                 **standard_kwargs,
             )
 
-            file_task.status = TaskStatus.COMPLETED
-            file_task.result = result
-            file_task.updated_at = time.time()
-            upload_task.successful_files += 1
+            if result.get("status") == "error":
+                file_task.status = TaskStatus.FAILED
+                file_task.error = result.get("error", "Failed to process document")
+                file_task.updated_at = time.time()
+                upload_task.failed_files += 1
+            else:
+                file_task.status = TaskStatus.COMPLETED
+                file_task.result = result
+                file_task.updated_at = time.time()
+                upload_task.successful_files += 1
 
         except Exception as e:
             file_task.status = TaskStatus.FAILED
@@ -844,6 +850,14 @@ async def process_item(self, upload_task: UploadTask, item: str, file_task: File
                         allowed_users=allowed_users,
                         allowed_groups=allowed_groups,
                     )
+                    # Langflow returns "success" even when no text was extracted
+                    # (e.g. image files without OCR). Verify the document actually
+                    # landed in OpenSearch before declaring success.
+                    if not await self.check_document_exists(document.id, opensearch_client):
+                        result = {
+                            "status": "error",
+                            "error": "No text content could be extracted from document",
+                        }
                 else:
                     # Standard OpenRAG processing pipeline (process_document_standard)
                     standard_kwargs: dict[str, Any] = {}
@@ -892,10 +906,16 @@ async def process_item(self, upload_task: UploadTask, item: str, file_task: File
                         }
                     )
 
-            file_task.status = TaskStatus.COMPLETED
-            file_task.result = result
-            file_task.updated_at = time.time()
-            upload_task.successful_files += 1
+            if result.get("status") == "error":
+                file_task.status = TaskStatus.FAILED
+                file_task.error = result.get("error", "Failed to process document")
+                file_task.updated_at = time.time()
+                upload_task.failed_files += 1
+            else:
+                file_task.status = TaskStatus.COMPLETED
+                file_task.result = result
+                file_task.updated_at = time.time()
+                upload_task.successful_files += 1
 
         except Exception as e:
             file_task.status = TaskStatus.FAILED
@@ -970,9 +990,14 @@ async def process_item(self, upload_task: UploadTask, item: str, file_task: File
                 )
 
                 result["path"] = f"s3://{self.bucket}/{item}"
-                file_task.status = TaskStatus.COMPLETED
-                file_task.result = result
-                upload_task.successful_files += 1
+                if result.get("status") == "error":
+                    file_task.status = TaskStatus.FAILED
+                    file_task.error = result.get("error", "Failed to process document")
+                    upload_task.failed_files += 1
+                else:
+                    file_task.status = TaskStatus.COMPLETED
+                    file_task.result = result
+                    upload_task.successful_files += 1
 
         except Exception as e:
             file_task.status = TaskStatus.FAILED
@@ -1106,11 +1131,20 @@ async def process_item(self, upload_task: UploadTask, item: str, file_task: File
                 file_task=file_task,
             )
 
-            # Update task with success
-            file_task.status = TaskStatus.COMPLETED
-            file_task.result = result
-            file_task.updated_at = time.time()
-            upload_task.successful_files += 1
+            # Langflow returns "success" even when no text was extracted.
+            # Verify the document actually landed in OpenSearch.
+            file_hash = hash_id(item)
+            if not await self.check_document_exists(file_hash, opensearch_client):
+                file_task.status = TaskStatus.FAILED
+                file_task.error = "No text content could be extracted from document"
+                file_task.updated_at = time.time()
+                upload_task.failed_files += 1
+            else:
+                # Update task with success
+                file_task.status = TaskStatus.COMPLETED
+                file_task.result = result
+                file_task.updated_at = time.time()
+                upload_task.successful_files += 1
 
         except Exception as e:
             # Update task with failure
diff --git a/src/services/task_service.py b/src/services/task_service.py
index 521444669..1aaf11a04 100644
--- a/src/services/task_service.py
+++ b/src/services/task_service.py
@@ -64,11 +64,22 @@
 )
 
 
+# Raster image formats that require OCR to produce any text content.
+_OCR_REQUIRED_EXTENSIONS = frozenset({"bmp", "jpeg", "jpg", "png", "tiff", "webp"})
+
+
 def _is_non_retryable_file_error(error: str) -> bool:
     lowered = error.lower()
     return any(marker in lowered for marker in _NON_RETRYABLE_FILE_ERROR_MARKERS)
 
 
+def _is_ocr_required_file(filename: str) -> bool:
+    """Return True if the file is a raster image that requires OCR to produce text."""
+    if not filename or "." not in filename:
+        return False
+    return filename.rsplit(".", 1)[-1].lower() in _OCR_REQUIRED_EXTENSIONS
+
+
 def _is_transient_connectivity_error(error: str) -> bool:
     lowered = error.lower()
     return any(marker in lowered for marker in _TRANSIENT_CONNECTIVITY_ERROR_MARKERS)
@@ -958,6 +969,22 @@ def _infer_failure_metadata(self, file_task: FileTask) -> dict | None:
 
         # First, check if the error is non-retryable based on common markers
         if _is_non_retryable_file_error(error):
+            # Image files that produced no text almost certainly failed because OCR
+            # is disabled — not because the file is corrupted. Give a targeted tip.
+            filename = file_task.filename or file_task.file_path or ""
+            if "no text content could be extracted" in error.lower() and _is_ocr_required_file(
+                filename
+            ):
+                return {
+                    "component": "docling",
+                    "failure_phase": "parsing",
+                    "user_facing_message": (
+                        "No text content could be extracted from this image file. "
+                        "Enable OCR in Settings > Knowledge Base and retry ingestion."
+                    ),
+                    "actionable_by": "RETRYABLE",
+                }
+
             if phase == IngestionPhase.LANGFLOW:
                 component = "langflow"
                 failure_phase = "unknown"