diff --git a/app/integrations/llm/prompt.py b/app/integrations/llm/prompt.py
index 4d6a06b..e5397d5 100644
--- a/app/integrations/llm/prompt.py
+++ b/app/integrations/llm/prompt.py
@@ -7,6 +7,7 @@ from integrations.llm.schemas.report import (
     YouTubeDiagnosisInput, YouTubeDiagnosisOutput,
     BrandConsistencyInput, BrandConsistencyOutput,
     TransformationInput, TransformationProposal,
+    RoadmapInput, RoadmapOutput,
 )
 from integrations.llm.schemas.plan import PlanInput, PlanOutput
 from integrations.llm.schemas.market import (
@@ -114,3 +115,10 @@ transformation_prompt = Prompt(
     input_class=TransformationInput,
     output_class=TransformationProposal,
 )
+
+roadmap_prompt = Prompt(
+    file_name="roadmap_prompt.txt",
+    prompt_model="REPORT_MODEL",
+    input_class=RoadmapInput,
+    output_class=RoadmapOutput,
+)
diff --git a/app/integrations/llm/schemas/report.py b/app/integrations/llm/schemas/report.py
index f9dc896..be3be9b 100644
--- a/app/integrations/llm/schemas/report.py
+++ b/app/integrations/llm/schemas/report.py
@@ -368,6 +368,17 @@ class CriticalIssuesOutput(BaseModel):
     diagnosis: list[DiagnosisItem]
 
 
+# --- Roadmap ---
+
+class RoadmapInput(BaseModel):
+    clinic_name: str | None = None
+    data: str | None = None
+
+
+class RoadmapOutput(BaseModel):
+    roadmap: list[RoadmapMonth]
+
+
 # --- Transformation ---
 
 class TransformationInput(BaseModel):
diff --git a/app/integrations/llm/temp-prompt/roadmap_prompt.txt b/app/integrations/llm/temp-prompt/roadmap_prompt.txt
new file mode 100644
index 0000000..0a11d48
--- /dev/null
+++ b/app/integrations/llm/temp-prompt/roadmap_prompt.txt
@@ -0,0 +1,14 @@
+다음은 성형외과/피부과 {clinic_name} 의 전 채널 수집 데이터입니다.
+
+{data}
+
+위 데이터를 바탕으로 이 병원의 3개월 마케팅 실행 로드맵을 수립해줘.
+month 1, 2, 3 각각 하나씩, 총 3개 항목을 포함한 roadmap JSON 배열로 출력해줘.
+
+각 항목은 아래 형식을 따라줘:
+- month: 월 번호 (1, 2, 3)
+- title: 해당 월의 핵심 테마 (예: "브랜드 정비")
+- subtitle: 한 줄 부제 (예: "기반 구축 — 로고·계정 통일")
+- tasks: 실행 과제 목록, 각 과제는 task(string)와 completed(false)로 구성
+
+출처 번호([1], [2] 등)는 포함하지 마.
diff --git a/app/services/analysis.py b/app/services/analysis.py
index b6d67cc..2774fdc 100644
--- a/app/services/analysis.py
+++ b/app/services/analysis.py
@@ -8,8 +8,8 @@ from common.db.run import select_run, update_run_report, update_run_plan
 from common.db.source import select_run_raw_data, select_run_mainpage_url
 from common.db.market import select_market
 from integrations.llm.llm_service import LLMService
-from integrations.llm.prompt import report_prompt, plan_prompt, youtube_diagnosis_prompt, brand_consistency_prompt, critical_issues_prompt, transformation_prompt
-from integrations.llm.schemas.report import ReportOutput, ClinicSnapshot, YouTubeAudit, BrandConsistencyOutput, CriticalIssuesOutput, DiagnosisItem, TransformationProposal
+from integrations.llm.prompt import report_prompt, plan_prompt, youtube_diagnosis_prompt, brand_consistency_prompt, critical_issues_prompt, transformation_prompt, roadmap_prompt
+from integrations.llm.schemas.report import ReportOutput, ClinicSnapshot, YouTubeAudit, BrandConsistencyOutput, CriticalIssuesOutput, DiagnosisItem, TransformationProposal, RoadmapOutput, RoadmapMonth
 from integrations.llm.schemas.plan import PlanOutput
 
 logger = logging.getLogger(__name__)
@@ -208,6 +208,17 @@ async def _build_youtube_audit(youtube: dict) -> dict:
     return YouTubeAudit.model_validate(yt_patch).model_dump()
 
 
+async def _build_roadmap(analysis_run_id: str, raw: dict) -> list[dict]:
+    result: RoadmapOutput = await LLMService(provider="perplexity").generate(
+        roadmap_prompt,
+        {
+            "clinic_name": (raw.get("mainpage") or {}).get("clinicName"),
+            "data":        json.dumps(raw, ensure_ascii=False),
+        },
+    )
+    return [RoadmapMonth.model_validate(item).model_dump() for item in result.roadmap]
+
+
 async def _build_transformation(analysis_run_id: str, raw: dict) -> dict:
     result: TransformationProposal = await LLMService(provider="perplexity").generate(
         transformation_prompt,
@@ -267,6 +278,7 @@ async def _build_overrides(analysis_run_id: str) -> dict:
     brand_patch = brand.model_dump()["brand_inconsistencies"]
     critical_issues = await _build_critical_issues(analysis_run_id, raw)
     transformation = await _build_transformation(analysis_run_id, raw)
+    roadmap = await _build_roadmap(analysis_run_id, raw)
 
     fb_patch: dict = {}
     if fb_pages:
@@ -287,6 +299,8 @@ async def _build_overrides(analysis_run_id: str) -> dict:
         overrides["problem_diagnosis"] = critical_issues
     if transformation:
         overrides["transformation"] = transformation
+    if roadmap:
+        overrides["roadmap"] = roadmap
     return overrides