diff --git a/cognee/tasks/feedback/generate_improved_answers.py b/cognee/tasks/feedback/generate_improved_answers.py
new file mode 100644
index 000000000..88cbfae8c
--- /dev/null
+++ b/cognee/tasks/feedback/generate_improved_answers.py
@@ -0,0 +1,132 @@
+from __future__ import annotations
+
+from typing import Dict, List, Optional, Tuple
+from pydantic import BaseModel
+
+from cognee.infrastructure.llm import LLMGateway
+from cognee.infrastructure.llm.prompts.read_query_prompt import read_query_prompt
+from cognee.modules.graph.utils import resolve_edges_to_text
+from cognee.shared.logging_utils import get_logger
+
+from .utils import create_retriever
+
+
+class ImprovedAnswerResponse(BaseModel):
+    """Response model for improved answer generation containing answer and explanation."""
+
+    answer: str
+    explanation: str
+
+
+logger = get_logger("generate_improved_answers")
+
+
+def _validate_input_data(feedback_interactions: List[Dict]) -> bool:
+    """Validate that input contains required fields for all items."""
+    required_fields = [
+        "question",
+        "answer",
+        "context",
+        "feedback_text",
+        "feedback_id",
+        "interaction_id",
+    ]
+    return all(
+        all(item.get(field) is not None for field in required_fields)
+        for item in feedback_interactions
+    )
+
+
+def _render_reaction_prompt(
+    question: str, context: str, wrong_answer: str, negative_feedback: str
+) -> str:
+    """Render the feedback reaction prompt with provided variables."""
+    prompt_template = read_query_prompt("feedback_reaction_prompt.txt")
+    return prompt_template.format(
+        question=question,
+        context=context,
+        wrong_answer=wrong_answer,
+        negative_feedback=negative_feedback,
+    )
+
+
+async def _generate_improved_answer_for_single_interaction(
+    feedback_interaction: Dict, retriever, reaction_prompt_location: str
+) -> Optional[Dict]:
+    """Generate improved answer for a single feedback-interaction pair using structured retriever completion."""
+    try:
+        question_text = feedback_interaction["question"]
+        original_answer_text = feedback_interaction["answer"]
+        context_text = feedback_interaction["context"]
+        feedback_text = feedback_interaction["feedback_text"]
+
+        query_text = _render_reaction_prompt(
+            question_text, context_text, original_answer_text, feedback_text
+        )
+
+        retrieved_context = await retriever.get_context(query_text)
+        completion, new_context_text = await retriever.get_structured_completion(
+            query=query_text, context=retrieved_context, response_model=ImprovedAnswerResponse
+        )
+
+        if completion:
+            return {
+                **feedback_interaction,
+                "improved_answer": completion.answer,
+                "new_context": new_context_text,
+                "explanation": completion.explanation,
+            }
+        else:
+            logger.warning(
+                "Failed to get structured completion from retriever", question=question_text
+            )
+            return None
+
+    except Exception as exc:  # noqa: BLE001
+        logger.error(
+            "Failed to generate improved answer",
+            error=str(exc),
+            question=feedback_interaction.get("question"),
+        )
+        return None
+
+
+async def generate_improved_answers(
+    feedback_interactions: List[Dict],
+    retriever_name: str = "graph_completion_cot",
+    top_k: int = 20,
+    reaction_prompt_location: str = "feedback_reaction_prompt.txt",
+) -> List[Dict]:
+    """Generate improved answers using configurable retriever and LLM."""
+    if not feedback_interactions:
+        logger.info("No feedback interactions provided; returning empty list")
+        return []
+
+    if not _validate_input_data(feedback_interactions):
+        logger.error("Input data validation failed; missing required fields")
+        return []
+
+    retriever = create_retriever(
+        retriever_name=retriever_name,
+        top_k=top_k,
+        user_prompt_path="graph_context_for_question.txt",
+        system_prompt_path="answer_simple_question.txt",
+    )
+
+    improved_answers: List[Dict] = []
+    successful_count = 0
+    failed_count = 0
+
+    for feedback_interaction in feedback_interactions:
+        result = await _generate_improved_answer_for_single_interaction(
+            feedback_interaction, retriever, reaction_prompt_location
+        )
+
+        if result:
+            improved_answers.append(result)
+            successful_count += 1
+        else:
+            failed_count += 1
+
+    logger.info("Generated improved answers", successful=successful_count, failed=failed_count)
+    return improved_answers