diff --git a/src/main/java/DiffLens/back_end/domain/panel/service/PanelInfoCacheService.java b/src/main/java/DiffLens/back_end/domain/panel/service/PanelInfoCacheService.java
new file mode 100644
index 0000000..897ac9a
--- /dev/null
+++ b/src/main/java/DiffLens/back_end/domain/panel/service/PanelInfoCacheService.java
@@ -0,0 +1,14 @@
+package DiffLens.back_end.domain.panel.service;
+
+import DiffLens.back_end.domain.panel.entity.Panel;
+import DiffLens.back_end.global.redis.CacheService;
+
+/**
+ *
+ * 패널 정보에 대한 캐시 정보를 다루는 service interface
+ *
+ * @param <T> 캐시로 다룰 데이터
+ */
+public interface PanelInfoCacheService<T> extends CacheService<T, Panel> {
+
+}
diff --git a/src/main/java/DiffLens/back_end/domain/panel/service/PanelInfoCacheServiceImpl.java b/src/main/java/DiffLens/back_end/domain/panel/service/PanelInfoCacheServiceImpl.java
new file mode 100644
index 0000000..4e0e333
--- /dev/null
+++ b/src/main/java/DiffLens/back_end/domain/panel/service/PanelInfoCacheServiceImpl.java
@@ -0,0 +1,38 @@
+package DiffLens.back_end.domain.panel.service;
+
+import DiffLens.back_end.domain.panel.entity.Panel;
+import DiffLens.back_end.domain.search.repository.cache.RedisRecommendationCacheRepository;
+import lombok.RequiredArgsConstructor;
+
+/**
+ * 패널 정보 캐싱 전략
+ *
+ * - 패널 정보는 유저 당 캐싱하지 않고, 서비스 전반적으로 저장합니다.
+ *
+ */
+@RequiredArgsConstructor
+public class PanelInfoCacheServiceImpl implements PanelInfoCacheService<Panel>{
+
+    private static final Integer TTL = 10;
+
+    // 캐시 정보를 관리하는 repository
+    private final RedisRecommendationCacheRepository cacheRepository;
+
+    // 캐시 Key 접두사
+    private static final String CACHE_KEY_PREFIX = "search:recommend:"; // search:recommend:{memberId} 형식으로 key 지정할 예정
+
+    @Override
+    public Panel getCacheInfo(Panel key) {
+
+        return null;
+
+    }
+
+    @Override
+    public void saveCacheInfo(Panel data, Panel cacheInfo) {
+
+    }
+
+
+
+}
diff --git a/src/main/java/DiffLens/back_end/domain/search/controller/SearchController.java b/src/main/java/DiffLens/back_end/domain/search/controller/SearchController.java
index 4bcef56..e01140b 100644
--- a/src/main/java/DiffLens/back_end/domain/search/controller/SearchController.java
+++ b/src/main/java/DiffLens/back_end/domain/search/controller/SearchController.java
@@ -1,6 +1,5 @@
 package DiffLens.back_end.domain.search.controller;
 
-import DiffLens.back_end.domain.search.dto.ChartDTO;
 import DiffLens.back_end.domain.search.dto.SearchRequestDTO;
 import DiffLens.back_end.domain.search.dto.SearchResponseDTO;
 import DiffLens.back_end.domain.search.service.interfaces.SearchHistoryService;
@@ -30,18 +29,38 @@ public class SearchController {
         private final SearchRecommendService searchRecommendService;
 
         @PostMapping
-        @Operation(summary = "자연어 검색 ( 자연어 쿼리 직접 입력 ) ( ai 연동 전 )", description = """
-
+        @Operation(summary = "자연어 검색 ( 자연어 쿼리 직접 입력 ) ( ai 연동 완료, 차트 포함 )", description = """
                         ## 개요
-                        자연어 검색 API 입니다.
+                        자연어 검색 API 입니다. AI 서버를 통해 검색을 수행하고, 검색 결과에 대한 차트 추천을 받아 반환합니다.
 
                         ## request body
                         - 검색 모드와 필터 항목들은 노션에 정리하여 올리겠습니다.
                         - 필터에는 Filter Code 를 넣어주세요. ex) 101, 203, 305 ...
 
-                        ## 응답
-                        검색 결과에 개별응답은 포함하지 않았습니다. 개별 응답 데이터 API를 조회해야 합니다.
-
+                        ## 응답 구조
+                        - **summary**: 검색 결과 요약 정보 (총 응답자 수, 평균 연령, 신뢰도 등)
+                        - **applied_filters_summary**: 적용된 필터 목록
+                        - **main_chart**: 메인 차트 데이터 (amCharts 형식)
+                          - `chart_type`: 차트 타입 (pie, donut, column, bar, map, stacked-bar, infographic 등)
+                          - `metric`: 차트를 생성한 메트릭 (age_group, gender, residence 등)
+                          - `title`: 차트 제목
+                          - `reasoning`: 차트 선택 이유 (메인 차트에만 제공)
+                          - `data`: 차트 데이터 포인트 배열
+                        - **sub_charts**: 서브 차트 데이터 배열 (최대 2개, amCharts 형식)
+                          - 메인 차트와 동일한 구조이지만 `reasoning`은 null
+
+                        ## 차트 타입
+                        - **pie**: 원형 차트 (2-5개 카테고리)
+                        - **donut**: 도넛 차트 (4-8개 카테고리)
+                        - **column**: 세로 막대 차트 (8개 이상 카테고리)
+                        - **bar**: 가로 막대 차트 (레이블이 긴 경우)
+                        - **map**: 지도 차트 (지역 데이터)
+                        - **stacked-bar**: 누적 가로 막대 차트 (연령대별 성별 분포 등)
+                        - **infographic**: 인포그래픽 차트 (직업별 성별 비율 등)
+
+                        ## 참고사항
+                        - 검색 결과에 개별응답은 포함하지 않았습니다. 개별 응답 데이터 API를 조회해야 합니다.
+                        - 차트는 AI 서버에서 자동으로 추천되며, 검색 결과의 특성에 따라 최적의 차트 타입이 선택됩니다.
                         """)
         public ApiResponse<SearchResponseDTO.SearchResult> naturalLanguage(
                         @RequestBody @Valid SearchRequestDTO.NaturalLanguage request) {
@@ -50,20 +69,21 @@ public ApiResponse<SearchResponseDTO.SearchResult> naturalLanguage(
         }
 
         @PostMapping("/recommended/{recommendedId}")
-        @Operation(summary = "추천 검색어로 검색 ( ai가 추천해준 검색 정보로 검색 ) ( ai X )", description = """
-
+        @Operation(summary = "추천 검색어로 검색 ( ai가 추천해준 검색 정보로 검색 ) ( ai 연동 완료, 차트 포함 )", description = """
                         ## 개요
-                        AI가 추천해준 검색 정보로 검색합니다.
+                        AI가 추천해준 검색 정보로 검색합니다. 자연어 검색 API와 동일한 응답 구조를 반환하며, 차트도 포함됩니다.
 
                         ## 요청
                         - 맞춤 검색 추천 api 호출로 얻은 결과 중 recommendations에 포함된 검색 정보의 id를 recommendedId에 넣어 요청하면 됩니다.
                         - 검색 정보는 DB가 아닌 캐시에 저장되어 일정 시간이 지나면 올바른 recommendedId로 요청해도 오류가 발생합니다.
-                        - 만료되었다는 응답이 발생하면 '맞춤 검색 추천' api를 다시 호출하거나,\n
+                        - 만료되었다는 응답이 발생하면 '맞춤 검색 추천' api를 다시 호출하거나,
                           추천 검색어 api에서 응답받은 title 혹은 query를 이용해서 자연어 검색 api를 호출하여 검색해주세요.
 
                         ## 응답
                         자연어 검색과 동일한 형태의 응답을 보냅니다.
-
+                        - **main_chart**: 메인 차트 데이터 (amCharts 형식)
+                        - **sub_charts**: 서브 차트 데이터 배열 (최대 2개, amCharts 형식)
+                        - 자세한 차트 구조는 자연어 검색 API 설명을 참고하세요.
                         """)
         public ApiResponse<SearchResponseDTO.SearchResult> recommendedSearch(
                         @PathVariable("recommendedId") Long recommendedId) {
@@ -185,12 +205,14 @@ public ApiResponse<SearchResponseDTO.EachResponses> eachResponsesTest(
         }
 
         @GetMapping("/recommended")
-        @Operation(summary = "맞춤 검색 추천 ( ai 연동 전 )", description = "유저 온보딩 정보, 검색기록을 토대로 검색어를 추천합니다.")
-        public ApiResponse<SearchResponseDTO.Recommends> refine() {
+        @Operation(summary = "맞춤 검색 추천 ( ai 연동 완료 )", description = "유저 온보딩 정보, 검색기록을 토대로 검색어를 추천합니다.")
+        public ApiResponse<SearchResponseDTO.Recommends> recommendation() {
                 SearchResponseDTO.Recommends recommendations = searchRecommendService.getRecommendations();
                 return ApiResponse.onSuccess(recommendations);
         }
 
+        /** ------ 👇 아래는 미제공 API 👇 ------ **/
+
         @GetMapping("/recommended/test")
         @Operation(summary = "맞춤 검색 추천 (테스트용)", description = """
                         ## 개요
@@ -255,6 +277,9 @@ public ApiResponse<SearchResponseDTO.SearchResult> refine(
 
                         ## 응답
                         POST /search API와 동일한 응답 형식입니다.
+                        - **main_chart**: null (테스트용이므로 차트 미포함)
+                        - **sub_charts**: null (테스트용이므로 차트 미포함)
+                        - 실제 API에서는 서브서버로부터 차트 데이터를 받아옵니다.
                         """)
         public ApiResponse<SearchResponseDTO.SearchResult> testSearch() {
                 // Summary 생성
@@ -280,74 +305,16 @@ public ApiResponse<SearchResponseDTO.SearchResult> testSearch() {
                                 .displayValue("남성")
                                 .build());
 
-                // Pie Chart 생성 (도넛 차트: 차 브랜드 분포)
-                ChartDTO.Graph pieChart = ChartDTO.Graph.builder()
-                                .chartId("pie_chart_001")
-                                .reason("20대 남성의 차 브랜드 분포를 시각화하기 위해 도넛 차트를 사용했습니다.")
-                                .chartType("PIE")
-                                .title("20대 남성이 타는 차 브랜드 분포")
-                                .xAxis(null)
-                                .yAxis(null)
-                                .dataPoints(List.of(
-                                                ChartDTO.DataPoint.builder().label("기아").value(40).build(),
-                                                ChartDTO.DataPoint.builder().label("현대자동차").value(35).build(),
-                                                ChartDTO.DataPoint.builder().label("테슬라").value(20).build(),
-                                                ChartDTO.DataPoint.builder().label("BMW").value(5).build()))
-                                .build();
-
-                // Chart 1: 직업 분포 (바 차트)
-                ChartDTO.Graph jobChart = ChartDTO.Graph.builder()
-                                .chartId("bar_chart_001")
-                                .reason("직업 분포를 월별로 비교하기 위해 바 차트를 사용했습니다.")
-                                .chartType("BAR")
-                                .title("직업 분포")
-                                .xAxis("월")
-                                .yAxis("인원수")
-                                .dataPoints(List.of(
-                                                ChartDTO.DataPoint.builder().label("Jan").value(9).build(),
-                                                ChartDTO.DataPoint.builder().label("Feb").value(10).build(),
-                                                ChartDTO.DataPoint.builder().label("Mar").value(8).build(),
-                                                ChartDTO.DataPoint.builder().label("Apr").value(8).build(),
-                                                ChartDTO.DataPoint.builder().label("May").value(9).build(),
-                                                ChartDTO.DataPoint.builder().label("Jun").value(10).build(),
-                                                ChartDTO.DataPoint.builder().label("Jul").value(7).build(),
-                                                ChartDTO.DataPoint.builder().label("Aug").value(7).build(),
-                                                ChartDTO.DataPoint.builder().label("Sep").value(6).build(),
-                                                ChartDTO.DataPoint.builder().label("Oct").value(8).build(),
-                                                ChartDTO.DataPoint.builder().label("Nov").value(8).build(),
-                                                ChartDTO.DataPoint.builder().label("Dec").value(9).build()))
-                                .build();
-
-                // Chart 2: 월평균 개인소득 (라인 차트)
-                ChartDTO.Graph incomeChart = ChartDTO.Graph.builder()
-                                .chartId("line_chart_001")
-                                .reason("월평균 개인소득의 추이를 보기 위해 라인 차트를 사용했습니다.")
-                                .chartType("LINE")
-                                .title("월평균 개인소득")
-                                .xAxis("월")
-                                .yAxis("소득 (만원)")
-                                .dataPoints(List.of(
-                                                ChartDTO.DataPoint.builder().label("Jan").value(450).build(),
-                                                ChartDTO.DataPoint.builder().label("Feb").value(550).build(),
-                                                ChartDTO.DataPoint.builder().label("Mar").value(400).build(),
-                                                ChartDTO.DataPoint.builder().label("Apr").value(600).build(),
-                                                ChartDTO.DataPoint.builder().label("May").value(500).build(),
-                                                ChartDTO.DataPoint.builder().label("Jun").value(700).build(),
-                                                ChartDTO.DataPoint.builder().label("Jul").value(650).build(),
-                                                ChartDTO.DataPoint.builder().label("Aug").value(750).build(),
-                                                ChartDTO.DataPoint.builder().label("Sep").value(700).build(),
-                                                ChartDTO.DataPoint.builder().label("Oct").value(800).build(),
-                                                ChartDTO.DataPoint.builder().label("Nov").value(900).build(),
-                                                ChartDTO.DataPoint.builder().label("Dec").value(1050).build()))
-                                .build();
+                // 차트 데이터는 실제 API에서는 서브서버로부터 받아옵니다.
+                // 테스트용으로 null 처리
 
                 // SearchResult 생성
                 SearchResponseDTO.SearchResult result = SearchResponseDTO.SearchResult.builder()
                                 .searchId(999L) // 테스트용 ID
                                 .summary(summary)
                                 .appliedFiltersSummary(appliedFilters)
-                                .pie(pieChart)
-                                .charts(List.of(jobChart, incomeChart))
+                                .mainChart(null) // 차트는 서브서버에서 받아옴
+                                .subCharts(null)
                                 .build();
 
                 return ApiResponse.onSuccess(result);
diff --git a/src/main/java/DiffLens/back_end/domain/search/converter/SummaryDtoConverter.java b/src/main/java/DiffLens/back_end/domain/search/converter/SummaryDtoConverter.java
index acf3201..5dc8d8a 100644
--- a/src/main/java/DiffLens/back_end/domain/search/converter/SummaryDtoConverter.java
+++ b/src/main/java/DiffLens/back_end/domain/search/converter/SummaryDtoConverter.java
@@ -22,10 +22,26 @@ public SearchResponseDTO.SearchResult.Summary requestToDto(MainSearchResponse re
                 .averageAge(getAgeAvg(response))
                 .dataCaptureDate(getCurrentDate())
                 .confidenceLevel(null)
+                .confidenceLevel(getConfidencePercent(response))
 //                .confidenceLevel(response.getAccuracy() != null ? response.getAccuracy().intValue() : null)
                 .build();
     }
 
+    private int getConfidencePercent(MainSearchResponse response) {
+        List<MainSearchResponse.PanelInfo> panels = response.getPanels();
+        if (panels.isEmpty()) return 0;
+
+        double sum = panels.stream()
+                .mapToDouble(MainSearchResponse.PanelInfo::getSimilarity)
+                .sum();
+
+        double avg = sum / panels.size();
+
+        return (int) Math.round(avg * 100); // 소수점 반올림 후 int로 변환
+    }
+
+
+
     private Double getAgeAvg(MainSearchResponse response) {
 
         List<MainSearchResponse.PanelInfo> panels = response.getPanels();
diff --git a/src/main/java/DiffLens/back_end/domain/search/dto/SearchResponseDTO.java b/src/main/java/DiffLens/back_end/domain/search/dto/SearchResponseDTO.java
index f283541..3171be1 100644
--- a/src/main/java/DiffLens/back_end/domain/search/dto/SearchResponseDTO.java
+++ b/src/main/java/DiffLens/back_end/domain/search/dto/SearchResponseDTO.java
@@ -27,12 +27,14 @@ public static class SearchResult {
         @JsonProperty("applied_filters_summary")
         private List<AppliedFilter> appliedFiltersSummary;
 
-        private ChartDTO.Graph pie;
+        @JsonProperty("main_chart")
+        private ChartData mainChart;
 
-        private List<ChartDTO.Graph> charts;
+        @JsonProperty("sub_charts")
+        private List<ChartData> subCharts;
 
-//        @JsonProperty("panel_data") // 개별 API로 분리
-//        private SearchPanelDTO.PanelData panelData;
+        // @JsonProperty("panel_data") // 개별 API로 분리
+        // private SearchPanelDTO.PanelData panelData;
 
         // 중간배열
         @Getter
@@ -65,6 +67,48 @@ public static class AppliedFilter {
             private String displayValue;
         }
 
+        @Getter
+        @Builder
+        @AllArgsConstructor
+        @NoArgsConstructor
+        public static class ChartData {
+            @JsonProperty("chart_type")
+            private String chartType;
+
+            private String metric;
+
+            private String title;
+
+            private String reasoning;
+
+            private List<ChartDataPoint> data;
+        }
+
+        @Getter
+        @Builder
+        @AllArgsConstructor
+        @NoArgsConstructor
+        public static class ChartDataPoint {
+            private String category;
+
+            private Integer value;
+
+            // stacked-bar, infographic 차트용 추가 필드들
+            private Integer male;
+
+            @JsonProperty("male_max")
+            private Integer maleMax;
+
+            private Integer female;
+
+            @JsonProperty("female_max")
+            private Integer femaleMax;
+
+            // map 차트용
+            private String id;
+
+            private String name;
+        }
 
     }
 
@@ -86,7 +130,7 @@ public static class EachResponses {
     @Builder
     @AllArgsConstructor
     @NoArgsConstructor
-    public static class ResponseValues{
+    public static class ResponseValues {
         @JsonProperty("respondent_id")
         private String respondentId;
         private String gender;
@@ -116,7 +160,7 @@ public static ResponseValues fromPanelDTO(PanelWithRawDataDTO panel, String conc
     @Builder
     @AllArgsConstructor
     @NoArgsConstructor
-    public static class Recommends{
+    public static class Recommends {
         private List<Recommend> recommendations;
     }
 
@@ -124,13 +168,10 @@ public static class Recommends{
     @Builder
     @AllArgsConstructor
     @NoArgsConstructor
-    public static class Recommend{
+    public static class Recommend {
         private Long id;
         private String title;
         private String description;
     }
 
-
-
-
 }
diff --git a/src/main/java/DiffLens/back_end/domain/search/repository/cache/RedisRecommendationCacheRepository.java b/src/main/java/DiffLens/back_end/domain/search/repository/cache/RedisRecommendationCacheRepository.java
index 8e4c25a..cc5166d 100644
--- a/src/main/java/DiffLens/back_end/domain/search/repository/cache/RedisRecommendationCacheRepository.java
+++ b/src/main/java/DiffLens/back_end/domain/search/repository/cache/RedisRecommendationCacheRepository.java
@@ -4,7 +4,7 @@
 import org.springframework.data.redis.core.RedisTemplate;
 import org.springframework.stereotype.Repository;
 
-import java.time.Duration;
+import java.util.concurrent.TimeUnit;
 import java.util.function.Supplier;
 
 /**
@@ -14,12 +14,13 @@
 @RequiredArgsConstructor
 public class RedisRecommendationCacheRepository {
 
+    private final static TimeUnit timeUnit = TimeUnit.MINUTES;
+
     private final RedisTemplate<String, Object> redisTemplate;
-    private static final Duration TTL = Duration.ofMinutes(10); // 유효기간
 
     // 저장
-    public void save(String key, Object value) {
-        redisTemplate.opsForValue().set(key, value, TTL);
+    public void save(String key, Object value, int ttl) {
+        redisTemplate.opsForValue().set(key, value, ttl, timeUnit);
     }
 
     @SuppressWarnings("unchecked")
@@ -27,11 +28,11 @@ public <T> T findByKey(String key){
         return (T) redisTemplate.opsForValue().get(key);
     }
 
-    public <T> T findOrElse(String key, Supplier<T> supplier) {
+    public <T> T findOrElse(String key, Supplier<T> supplier, int ttl) {
         T value = findByKey(key);
         if (value == null) {
             value = supplier.get();
-            save(key, value);
+            save(key, value, ttl);
         }
         return value;
     }
diff --git a/src/main/java/DiffLens/back_end/domain/search/service/implement/NaturalSearchService.java b/src/main/java/DiffLens/back_end/domain/search/service/implement/NaturalSearchService.java
index 2fa44cb..a9fc767 100644
--- a/src/main/java/DiffLens/back_end/domain/search/service/implement/NaturalSearchService.java
+++ b/src/main/java/DiffLens/back_end/domain/search/service/implement/NaturalSearchService.java
@@ -5,25 +5,17 @@
 import DiffLens.back_end.domain.panel.repository.PanelRepository;
 import DiffLens.back_end.domain.panel.repository.projection.PanelWithRawDataDTO;
 import DiffLens.back_end.domain.search.entity.Filter;
-import DiffLens.back_end.domain.search.enums.chart.ChartType;
 import DiffLens.back_end.domain.search.repository.FilterRepository;
-import DiffLens.back_end.domain.search.repository.SearchHistoryRepository;
 import DiffLens.back_end.global.fastapi.FastApiService;
-import DiffLens.back_end.global.fastapi.dto.request.FastNaturalLanguageRequestDTO;
 import DiffLens.back_end.global.fastapi.dto.request.MainSearchRequest;
-import DiffLens.back_end.global.fastapi.dto.response.FastNaturalLanguageResponseDTO;
+import DiffLens.back_end.global.fastapi.dto.response.FastChartResponseDTO;
 import DiffLens.back_end.domain.search.converter.SearchDtoConverter;
-import DiffLens.back_end.domain.search.dto.ChartDTO;
 import DiffLens.back_end.domain.search.dto.SearchRequestDTO;
 import DiffLens.back_end.domain.search.dto.SearchResponseDTO;
-import DiffLens.back_end.domain.search.entity.Chart;
 import DiffLens.back_end.domain.search.entity.SearchHistory;
-import DiffLens.back_end.domain.search.service.interfaces.ChartService;
 import DiffLens.back_end.domain.search.service.interfaces.SearchHistoryService;
 import DiffLens.back_end.domain.search.service.interfaces.SearchService;
 import DiffLens.back_end.global.fastapi.dto.response.MainSearchResponse;
-import DiffLens.back_end.global.responses.code.status.error.SearchStatus;
-import DiffLens.back_end.global.responses.exception.handler.ErrorHandler;
 import lombok.RequiredArgsConstructor;
 import org.springframework.stereotype.Service;
 import org.springframework.transaction.annotation.Transactional;
@@ -43,17 +35,13 @@ public class NaturalSearchService implements SearchService<SearchRequestDTO.Natu
     private final PanelRepository panelRepository;
     private final FilterRepository filterRepository;
     private final SearchHistoryService searchHistoryService;
-    private final ChartService chartService;
     private final FastApiService fastApiService;
 
     // converter들
     private final SearchDtoConverter<MainSearchResponse, SearchResponseDTO.SearchResult.Summary, List<PanelWithRawDataDTO>> summaryConverter;
     private final SearchDtoConverter<Void, List<SearchResponseDTO.SearchResult.AppliedFilter>, SearchHistory> filterConverter;
-    private final SearchDtoConverter<Void , ChartDTO.Graph, Chart> chartConverter;
-//    private final SearchDtoConverter<FastNaturalSearchResponseDTO.SearchResult, SearchPanelDTO.PanelData, List<PanelWithRawDataDTO>> panelResponseConverter;
 
     private final CurrentUserService currentUserService;
-    private final SearchHistoryRepository searchHistoryRepository;
 
     @Override
     @Transactional(readOnly = false)
@@ -97,32 +85,67 @@ public SearchResponseDTO.SearchResult search(SearchRequestDTO.NaturalLanguage re
         // SearchResult.AppliedFilter 생성
         List<SearchResponseDTO.SearchResult.AppliedFilter> appliedFiltersSummary = filterConverter.requestToDto(null, searchHistory);
 
-        // 차트 생성
-//        List<Chart> charts = chartService.makeChart(new FastNaturalLanguageResponseDTO.Data(), searchHistory, foundPanels); // TODO : 서브서버에서 차트 받아서 적용하기
-//        charts.forEach(searchHistory::addChart); // 연관관계 편의 메서드 호출
+        // 차트 추천 API 호출
+        FastChartResponseDTO.ChartRecommendationsResponse chartResponse = 
+                fastApiService.getChartRecommendations(searchHistory.getId());
 
-        // 차트 변환
-//        Chart pieChart = charts.stream().filter(chart -> chart.getChartType() == ChartType.PIE) // 상단 차트 ( PIE 하나 )를 변환하여 생성
-//                .findFirst().orElse(null);
-//        ChartDTO.Graph pie = chartConverter.requestToDto(null, pieChart);
-//
-//        List<ChartDTO.Graph> graphs = charts.stream() // PIE를 제외한 차트를 변환하여 List<Graph> 생성
-//                .filter(chart -> chart.getChartType() != ChartType.PIE)
-//                .map(chart -> chartConverter.requestToDto(null, chart))
-//                .toList();
-
-        // 개별 응답 데이터 처리 및 반환
-//        SearchPanelDTO.PanelData panelData = panelResponseConverter.requestToDto(response, foundPanels);
+        // ChartData 변환
+        SearchResponseDTO.SearchResult.ChartData mainChart = convertToChartData(chartResponse.getMainChart());
+        List<SearchResponseDTO.SearchResult.ChartData> subCharts = chartResponse.getSubCharts().stream()
+                .map(this::convertToChartData)
+                .toList();
 
         return SearchResponseDTO.SearchResult.builder()
                 .searchId(searchHistory.getId())
                 .summary(summary)
                 .appliedFiltersSummary(appliedFiltersSummary)
-                .pie(null) // TODO : fast api에서 받아서 적용하기
-                .charts(null)
-//                .panelData(panelData) // 개별 API로 분리
+                .mainChart(mainChart)
+                .subCharts(subCharts)
+                .build();
+
+    }
+
+    /**
+     * FastAPI ChartData를 SearchResponseDTO ChartData로 변환
+     */
+    private SearchResponseDTO.SearchResult.ChartData convertToChartData(
+            FastChartResponseDTO.ChartData fastChartData) {
+        if (fastChartData == null) {
+            return null;
+        }
+
+        List<SearchResponseDTO.SearchResult.ChartDataPoint> dataPoints = fastChartData.getData().stream()
+                .map(this::convertToChartDataPoint)
+                .toList();
+
+        return SearchResponseDTO.SearchResult.ChartData.builder()
+                .chartType(fastChartData.getChartType())
+                .metric(fastChartData.getMetric())
+                .title(fastChartData.getTitle())
+                .reasoning(fastChartData.getReasoning())
+                .data(dataPoints)
                 .build();
+    }
 
+    /**
+     * FastAPI ChartDataPoint를 SearchResponseDTO ChartDataPoint로 변환
+     */
+    private SearchResponseDTO.SearchResult.ChartDataPoint convertToChartDataPoint(
+            FastChartResponseDTO.ChartDataPoint fastDataPoint) {
+        if (fastDataPoint == null) {
+            return null;
+        }
+
+        return SearchResponseDTO.SearchResult.ChartDataPoint.builder()
+                .category(fastDataPoint.getCategory())
+                .value(fastDataPoint.getValue())
+                .male(fastDataPoint.getMale())
+                .maleMax(fastDataPoint.getMaleMax())
+                .female(fastDataPoint.getFemale())
+                .femaleMax(fastDataPoint.getFemaleMax())
+                .id(fastDataPoint.getId())
+                .name(fastDataPoint.getName())
+                .build();
     }
 
     // fast api에 보낼 요청 dto 생성
diff --git a/src/main/java/DiffLens/back_end/domain/search/service/implement/SearchRecommendCacheService.java b/src/main/java/DiffLens/back_end/domain/search/service/implement/RecommendSearchCacheServiceImpl.java
similarity index 74%
rename from src/main/java/DiffLens/back_end/domain/search/service/implement/SearchRecommendCacheService.java
rename to src/main/java/DiffLens/back_end/domain/search/service/implement/RecommendSearchCacheServiceImpl.java
index 9979b0e..f9c7547 100644
--- a/src/main/java/DiffLens/back_end/domain/search/service/implement/SearchRecommendCacheService.java
+++ b/src/main/java/DiffLens/back_end/domain/search/service/implement/RecommendSearchCacheServiceImpl.java
@@ -2,14 +2,16 @@
 
 import DiffLens.back_end.domain.members.entity.Member;
 import DiffLens.back_end.domain.search.repository.cache.RedisRecommendationCacheRepository;
-import DiffLens.back_end.domain.search.service.interfaces.SearchCacheService;
+import DiffLens.back_end.domain.search.service.interfaces.RecommendSearchCacheService;
 import DiffLens.back_end.global.fastapi.dto.response.FastHomeResponseDTO;
 import lombok.RequiredArgsConstructor;
 import org.springframework.stereotype.Service;
 
 @Service
 @RequiredArgsConstructor
-public class SearchRecommendCacheService implements SearchCacheService<FastHomeResponseDTO.Data> {
+public class RecommendSearchCacheServiceImpl implements RecommendSearchCacheService<FastHomeResponseDTO.HomeRecommend> {
+
+    private static final Integer TTL = 10;
 
     // 캐시 정보를 관리하는 repository
     private final RedisRecommendationCacheRepository cacheRepository;
@@ -19,7 +21,7 @@ public class SearchRecommendCacheService implements SearchCacheService<FastHomeR
 
     // 저장되어있는 추천정보를 꺼냄
     @Override
-    public FastHomeResponseDTO.Data getCacheInfo(Member member) {
+    public FastHomeResponseDTO.HomeRecommend getCacheInfo(Member member) {
 
         // 캐시에서 조회할 키를 생성
         String key = getKey(member);
@@ -30,8 +32,8 @@ public FastHomeResponseDTO.Data getCacheInfo(Member member) {
 
     // 추천정보를 캐시에 저장함
     @Override
-    public void saveCacheInfo(Member member, FastHomeResponseDTO.Data cacheInfo) {
-        cacheRepository.save(getKey(member), cacheInfo);
+    public void saveCacheInfo(Member member, FastHomeResponseDTO.HomeRecommend cacheInfo) {
+        cacheRepository.save(getKey(member), cacheInfo, TTL);
     }
 
     private String getKey(Member member) {
diff --git a/src/main/java/DiffLens/back_end/domain/search/service/implement/RecommendedSearchService.java b/src/main/java/DiffLens/back_end/domain/search/service/implement/RecommendedSearchService.java
index e0c28ea..8629923 100644
--- a/src/main/java/DiffLens/back_end/domain/search/service/implement/RecommendedSearchService.java
+++ b/src/main/java/DiffLens/back_end/domain/search/service/implement/RecommendedSearchService.java
@@ -5,7 +5,7 @@
 import DiffLens.back_end.domain.search.dto.SearchRequestDTO;
 import DiffLens.back_end.domain.search.dto.SearchResponseDTO;
 import DiffLens.back_end.domain.search.enums.mode.QuestionMode;
-import DiffLens.back_end.domain.search.service.interfaces.SearchCacheService;
+import DiffLens.back_end.domain.search.service.interfaces.RecommendSearchCacheService;
 import DiffLens.back_end.domain.search.service.interfaces.SearchService;
 import DiffLens.back_end.global.fastapi.dto.response.FastHomeResponseDTO;
 import DiffLens.back_end.global.responses.code.status.error.SearchStatus;
@@ -24,7 +24,7 @@ public class RecommendedSearchService implements SearchService<Long> {
 
     private final CurrentUserService currentUserService;
     private final SearchService<SearchRequestDTO.NaturalLanguage> naturalSearchService;
-    private final SearchCacheService<FastHomeResponseDTO.Data> recommendCacheService;
+    private final RecommendSearchCacheService<FastHomeResponseDTO.HomeRecommend> recommendCacheService;
 
     @Override
     public SearchResponseDTO.SearchResult search(Long recommendedId) {
@@ -33,7 +33,7 @@ public SearchResponseDTO.SearchResult search(Long recommendedId) {
         Member member = currentUserService.getCurrentUser();
 
         // 1. 캐시에 있으면 그거로 SearchRequestDTO.NaturalLanguage 객체 만듦
-        FastHomeResponseDTO.Data cacheInfo = recommendCacheService.getCacheInfo(member);
+        FastHomeResponseDTO.HomeRecommend cacheInfo = recommendCacheService.getCacheInfo(member);
         if (cacheInfo == null) { //
             throw new ErrorHandler(SearchStatus.RECOMMENDED_EXPIRED); // 멤버에 해당하는 추천 검색어 캐시가 만료된 경우
         }
@@ -44,8 +44,6 @@ public SearchResponseDTO.SearchResult search(Long recommendedId) {
                 .findFirst()
                 .orElseThrow(() -> new ErrorHandler(SearchStatus.RECOMMENDED_SEARCH_NOT_FOUND)); // 멤버에 해당하는 캐시 정보는 있지만 recommendedId가 잘못된 경우
 
-        // 2. SearchRequestDTO.NaturalLanguage 이거로 자연어 검색 호출 - naturalSearchService
-
         // 2-1. Recommendation -> SearchRequestDTO.NaturalLanguage 변환
         SearchRequestDTO.NaturalLanguage naturalRequestDTO = SearchRequestDTO.NaturalLanguage.builder()
                 .question(recommendation.getQuery())
@@ -53,7 +51,7 @@ public SearchResponseDTO.SearchResult search(Long recommendedId) {
                 .filters(new ArrayList<Long>()) // 일단 필터 없이...
                 .build();
 
-        // 2-1. SearchRequestDTO.NaturalLanguage로 기존 자연어 검색 서비스 메서드 호출 -> 반환
+        // . SearchRequestDTO.NaturalLanguage로 기존 자연어 검색 서비스 메서드 호출 -> 반환
         return naturalSearchService.search(naturalRequestDTO);
     }
 
diff --git a/src/main/java/DiffLens/back_end/domain/search/service/implement/SearchHistoryServiceImpl.java b/src/main/java/DiffLens/back_end/domain/search/service/implement/SearchHistoryServiceImpl.java
index 00c4158..dda093f 100644
--- a/src/main/java/DiffLens/back_end/domain/search/service/implement/SearchHistoryServiceImpl.java
+++ b/src/main/java/DiffLens/back_end/domain/search/service/implement/SearchHistoryServiceImpl.java
@@ -20,9 +20,11 @@
 import org.springframework.data.domain.Page;
 import org.springframework.data.domain.PageRequest;
 import org.springframework.data.domain.Pageable;
+import org.springframework.security.core.parameters.P;
 import org.springframework.stereotype.Service;
 
 import java.time.LocalDate;
+import java.util.Collections;
 import java.util.List;
 
 @Service
@@ -112,7 +114,7 @@ public SearchResponseDTO.EachResponses getEachResponses(Long searchHistoryId, In
 
         // Panel 목록 순회하며 응답보낼 데이터 파싱
         // panelIds와 concordanceRate의 순서쌍에 맞게 패널 정보와 일치율을 담음
-        List<SearchResponseDTO.ResponseValues> values = panelDtoList.stream()
+        List<SearchResponseDTO.ResponseValues> values = new java.util.ArrayList<>(panelDtoList.stream()
                 .map(panel -> {
                     int index = panelIds.indexOf(panel.getId()); //
                     String rate = (index != -1 && index < concordanceRate.size())
@@ -120,7 +122,10 @@ public SearchResponseDTO.EachResponses getEachResponses(Long searchHistoryId, In
 
                     return SearchResponseDTO.ResponseValues.fromPanelDTO(panel, rate);
                 })
-                .toList();
+                .toList());
+
+        // 유사도 기준 내림차순 정렬
+        values.sort( ( a, b ) -> b.getConcordanceRate().compareTo(a.getConcordanceRate()) );
 
         //페이징 정보 생성
         ResponsePageDTO.OffsetLimitPageInfo pageInfo = ResponsePageDTO.OffsetLimitPageInfo.from(panelDtoList);
diff --git a/src/main/java/DiffLens/back_end/domain/search/service/implement/SearchRecommendServiceImpl.java b/src/main/java/DiffLens/back_end/domain/search/service/implement/SearchRecommendServiceImpl.java
index 954ecb1..927a3d0 100644
--- a/src/main/java/DiffLens/back_end/domain/search/service/implement/SearchRecommendServiceImpl.java
+++ b/src/main/java/DiffLens/back_end/domain/search/service/implement/SearchRecommendServiceImpl.java
@@ -1,16 +1,11 @@
 package DiffLens.back_end.domain.search.service.implement;
 
 import DiffLens.back_end.domain.members.entity.Member;
-import DiffLens.back_end.domain.members.entity.Onboarding;
-import DiffLens.back_end.domain.members.enums.Industry;
-import DiffLens.back_end.domain.members.enums.Job;
-import DiffLens.back_end.domain.members.repository.OnboardingRepository;
 import DiffLens.back_end.domain.members.service.auth.CurrentUserService;
 import DiffLens.back_end.domain.search.dto.SearchResponseDTO;
-import DiffLens.back_end.domain.search.entity.SearchHistory;
-import DiffLens.back_end.domain.search.repository.SearchHistoryRepository;
-import DiffLens.back_end.domain.search.service.interfaces.SearchCacheService;
+import DiffLens.back_end.domain.search.service.interfaces.RecommendSearchCacheService;
 import DiffLens.back_end.domain.search.service.interfaces.SearchRecommendService;
+import DiffLens.back_end.domain.search.util.member.SearchMemberUtil;
 import DiffLens.back_end.global.fastapi.FastApiService;
 import DiffLens.back_end.global.fastapi.dto.request.FastHomeRequestDTO;
 import DiffLens.back_end.global.fastapi.dto.response.FastHomeResponseDTO;
@@ -25,12 +20,11 @@
 @RequiredArgsConstructor
 public class SearchRecommendServiceImpl implements SearchRecommendService {
 
+    private final SearchMemberUtil searchMemberUtil;
+
     private final FastApiService fastApiService;
     private final CurrentUserService currentUserService;
-    private final SearchCacheService<FastHomeResponseDTO.Data> recommendCacheService;
-
-    private final OnboardingRepository onboardingRepository;
-    private final SearchHistoryRepository searchHistoryRepository;
+    private final RecommendSearchCacheService<FastHomeResponseDTO.HomeRecommend> recommendCacheService;
 
     /**
      *
@@ -49,7 +43,7 @@ public SearchResponseDTO.Recommends getRecommendations() {
         Member member = currentUserService.getCurrentUser();
 
         // 1. 캐시에 존재하면 캐시에서 꺼내서 반환
-        FastHomeResponseDTO.Data cacheInfo = recommendCacheService.getCacheInfo(member);
+        FastHomeResponseDTO.HomeRecommend cacheInfo = recommendCacheService.getCacheInfo(member);
         if (cacheInfo != null) { // redis에 값이 있다면 ai 로직을 호출하지 않고 바로 return
             log.info("[API 호출중] 검색 추천 정보를 캐시에서 조회");
             return fastDtoToResponseList(cacheInfo);
@@ -57,67 +51,33 @@ public SearchResponseDTO.Recommends getRecommendations() {
 
         log.info("[API 호출중] 검색 추천 정보를 조회하기 위해 AI 로직 호출");
 
-        // 2. 온보딩 정보 조회
-        Onboarding onboarding = onboardingRepository.findByMember(member)
-                .orElse(Onboarding.builder()
-                        .job(Job.ETC_FREELANCER)
-                        .industry(Industry.ETC)
-                        .build()
-                ); // 없으면 그냥 기타 정보 들어있는 객체를 담아서 보냄
-
-        // 2-1. 온보딩 정보에서 직무(Job)와 직종(Industry) 추출 => HomeRecommendOnboarding 생성
-
-        FastHomeRequestDTO.HomeRecommendOnboarding onboardingResult = FastHomeRequestDTO.HomeRecommendOnboarding.builder()
-                .job(onboarding.getJob().getKrValue())
-                .industry(onboarding.getIndustry().getKrValue())
-                .build();
-
-        // 3. 검색기록 조회
-        List<SearchHistory> searchHistoryList = searchHistoryRepository.findByMember(member);
+        // 2. member 기반 요청 데이터 준비
+        FastHomeRequestDTO.HomeRecommendRequest fastRequestDTO = searchMemberUtil.makeRequest(member);
 
-        // 3-1. 검색기록 목록에서 검색내용 ( content ) 만 추출
-        List<String> searchContentList = searchHistoryList.stream()
-                .map(SearchHistory::getContent)
-                .toList();
-
-        // 4. 위에서 구한 것들로 요청 DTO 생성
-        FastHomeRequestDTO.HomeRecommendRequest fastRequestDTO = FastHomeRequestDTO.HomeRecommendRequest.builder()
-                .memberId(member.getId())
-                .onboarding(onboardingResult)
-                .recentSearches(searchContentList)
-                .build();
-
-        // 5. fast api 요청 후 받은 응답결과를 저장
+        // 3. fast api 요청 후, 응답결과를 저장
         FastHomeResponseDTO.HomeRecommend fastResponse = fastApiService.recommend(fastRequestDTO);
 
-        // 6. 클라이언트에게 보낼 DTO 생성 후
+        // 4. 클라이언트에게 보낼 DTO 생성 후
         SearchResponseDTO.Recommends result = fastDtoToResponseList(fastResponse);
-        recommendCacheService.saveCacheInfo(member, fastResponse.getData()); // 이후에 조회할 때 캐시(Redis)에서 조회하기 위해 캐시에 저장
+        recommendCacheService.saveCacheInfo(member, fastResponse); // 이후에 조회할 때 캐시(Redis)에서 조회하기 위해 캐시에 저장
 
-        // 7. 반환
+        // 5. 반환
         return result;
     }
 
-    // Fast api에서 받은 응답 객체를 클라이언트에게 응답보낼 dto로 변환
-    // FastHomeResponseDTO.HomeRecommend -> SearchResponseDTO.Recommends
-    private SearchResponseDTO.Recommends fastDtoToResponseList(FastHomeResponseDTO.HomeRecommend fastResponse) {
-        // 응답받은 객체에서 추천 객체만 뽑아냄
-        return fastDtoToResponseList(fastResponse.getData());
-    }
-
     // Fast api에서 받은 응답 객체를 클라이언트에게 응답보낼 dto로 변환
     // FastHomeResponseDTO.Data -> SearchResponseDTO.Recommends
-    private SearchResponseDTO.Recommends fastDtoToResponseList(FastHomeResponseDTO.Data recommedationData){
+    private SearchResponseDTO.Recommends fastDtoToResponseList(FastHomeResponseDTO.HomeRecommend recommendationResponse){
 
         // 응답받은 객체에서 추천 객체만 뽑아냄
-        List<FastHomeResponseDTO.Recommendation> recommendations = recommedationData.getRecommendations();
+        List<FastHomeResponseDTO.Recommendation> recommendations = recommendationResponse.getRecommendations();
 
         // 추천 객체제를 순회하며 Recommend( 클라이언트 DTO에 담기는 ) 목록 생성
         List<SearchResponseDTO.Recommend> recommendList = recommendations.stream()
                 .map(recommendation -> SearchResponseDTO.Recommend.builder()
                         .id(recommendation.getId())
-                        .title(recommendation.getTitle())
-                        .description(recommendation.getTitle())
+                        .title(recommendation.getQuery())
+                        .description(recommendation.getDescription())
                         .build()
                 ).toList();
 
diff --git a/src/main/java/DiffLens/back_end/domain/search/service/interfaces/RecommendSearchCacheService.java b/src/main/java/DiffLens/back_end/domain/search/service/interfaces/RecommendSearchCacheService.java
new file mode 100644
index 0000000..92a5c7b
--- /dev/null
+++ b/src/main/java/DiffLens/back_end/domain/search/service/interfaces/RecommendSearchCacheService.java
@@ -0,0 +1,16 @@
+package DiffLens.back_end.domain.search.service.interfaces;
+
+import DiffLens.back_end.domain.members.entity.Member;
+import DiffLens.back_end.global.redis.CacheService;
+
+/**
+ *
+ * 추천 데이터 캐시를 다루는 서비스 interface
+ *
+ * @param <T> 캐시로 다룰 데이터
+ */
+public interface RecommendSearchCacheService<T> extends CacheService<T, Member> {
+
+
+
+}
diff --git a/src/main/java/DiffLens/back_end/domain/search/service/interfaces/SearchCacheService.java b/src/main/java/DiffLens/back_end/domain/search/service/interfaces/SearchCacheService.java
deleted file mode 100644
index 344534a..0000000
--- a/src/main/java/DiffLens/back_end/domain/search/service/interfaces/SearchCacheService.java
+++ /dev/null
@@ -1,11 +0,0 @@
-package DiffLens.back_end.domain.search.service.interfaces;
-
-import DiffLens.back_end.domain.members.entity.Member;
-
-public interface SearchCacheService<T> {
-
-    T getCacheInfo(Member member);
-
-    void saveCacheInfo(Member member, T cacheInfo);
-
-}
diff --git a/src/main/java/DiffLens/back_end/domain/search/util/member/SearchMemberUtil.java b/src/main/java/DiffLens/back_end/domain/search/util/member/SearchMemberUtil.java
new file mode 100644
index 0000000..d2d82b6
--- /dev/null
+++ b/src/main/java/DiffLens/back_end/domain/search/util/member/SearchMemberUtil.java
@@ -0,0 +1,87 @@
+package DiffLens.back_end.domain.search.util.member;
+
+import DiffLens.back_end.domain.members.entity.Member;
+import DiffLens.back_end.domain.members.entity.Onboarding;
+import DiffLens.back_end.domain.members.enums.Industry;
+import DiffLens.back_end.domain.search.entity.SearchHistory;
+import DiffLens.back_end.domain.search.repository.SearchHistoryRepository;
+import DiffLens.back_end.global.fastapi.dto.request.FastHomeRequestDTO;
+import lombok.RequiredArgsConstructor;
+import org.springframework.stereotype.Component;
+
+import java.util.List;
+
+@Component
+@RequiredArgsConstructor
+public class SearchMemberUtil {
+
+    private static final int LIMIT = 6;
+    private static final int HISTORY_LIMIT = 50;
+
+    private final SearchHistoryRepository searchHistoryRepository;
+
+
+    /**
+     *
+     * 추천 검색에 필요한 요청 DTO 를 생성하여 반환합니다.
+     *
+     * 담긴 정보
+     * - 검색기록
+     * - 직업군
+     * - 제한
+     *
+     *
+     * @param member 현재 로그인한 유저
+     * @return Fast API에 요청할 DTO 객체
+     */
+    public FastHomeRequestDTO.HomeRecommendRequest makeRequest(Member member){
+
+        // 1. 온보딩 정보 조회 ( 직업군 )
+        Industry industry = getIndustry(member);
+
+        // 2. 검색기록 조회
+        List<SearchHistory> searchHistoryList = searchHistoryRepository.findByMember(member);
+        List<String> searchContentList = searchHistoryList.stream()
+                .map(SearchHistory::getContent)
+                .toList();
+
+        return FastHomeRequestDTO.HomeRecommendRequest.builder()
+                .recentSearches(searchContentList)
+                .limit(LIMIT)
+                .industry(industry.getKrValue())
+                .build();
+    }
+
+    /**
+     *
+     * 유저 정보를 조회해서 추천 검색어 조회
+     *
+     * 담긴 정보
+     * - 유저 ID
+     * - 검색기록 제한
+     * - 결과 제한
+     * - 직업군
+     *
+     * @param member 현래 로그인한 유저
+     * @return Fast API에 요청할 DTO
+     */
+    public FastHomeRequestDTO.HomeRecommendByMemberRequest makeRequestByMember(Member member){
+
+        return FastHomeRequestDTO.HomeRecommendByMemberRequest.builder()
+                .memberId(member.getId())
+                .limit(LIMIT)
+                .historyLimit(HISTORY_LIMIT)
+                .industry(getIndustry(member).getKrValue())
+                .build();
+
+    }
+
+    private static Industry getIndustry(Member member) {
+        // 1. 온보딩 정보 조회
+        Onboarding onboarding = member.getOnboarding();
+        Industry industry = onboarding.getIndustry();
+        return industry;
+    }
+
+
+}
diff --git a/src/main/java/DiffLens/back_end/global/fastapi/FastApiClient.java b/src/main/java/DiffLens/back_end/global/fastapi/FastApiClient.java
index 1b83173..b33a1d2 100644
--- a/src/main/java/DiffLens/back_end/global/fastapi/FastApiClient.java
+++ b/src/main/java/DiffLens/back_end/global/fastapi/FastApiClient.java
@@ -49,4 +49,30 @@ public <T, R> R sendRequest(FastApiRequestType type, T requestBody) {
         return block;
     }
 
+    /**
+     * PathVariable을 사용하는 GET 요청
+     *
+     * @param type fast api에 보낼 요청을 관리하는 enum - FastApiRequestType
+     * @param requestBody 요청 본문 (null 가능)
+     * @param pathVariables URI에 포함될 경로 변수들
+     * @return fast api 로부터 응답받은 데이터 ( R )
+     * @param <T> request body의 클래스
+     * @param <R> response body의 클래스
+     */
+    @LogExecutionTime("서브서버 호출 소요시간")
+    public <T, R> R sendRequestWithPathVariable(FastApiRequestType type, T requestBody, Object... pathVariables) {
+        R block = null;
+        try {
+            block = fastApiWebClient.get()
+                    .uri(type.getUri(), pathVariables)
+                    .retrieve()
+                    .bodyToMono((Class<R>) type.getResponseType())
+                    .block();
+        } catch (Exception e) {
+            throw new ErrorHandler(ErrorStatus.SUB_SERVER_ERROR);
+        }
+
+        return block;
+    }
+
 }
diff --git a/src/main/java/DiffLens/back_end/global/fastapi/FastApiRequestType.java b/src/main/java/DiffLens/back_end/global/fastapi/FastApiRequestType.java
index 5cd4c42..b155e20 100644
--- a/src/main/java/DiffLens/back_end/global/fastapi/FastApiRequestType.java
+++ b/src/main/java/DiffLens/back_end/global/fastapi/FastApiRequestType.java
@@ -9,15 +9,25 @@
 @AllArgsConstructor
 public enum FastApiRequestType {
 
+        // 검색
         NATURAL_SEARCH("/ai/search", FastNaturalLanguageRequestDTO.NaturalSearch.class,
                         FastNaturalLanguageResponseDTO.NaturalSearch.class),
         NATURAL_SEARCH2("/api/search/", MainSearchRequest.class,
-                MainSearchResponse.class),
+                        MainSearchResponse.class),
         RE_SEARCH("/api/re-search", FastReSearchRequestDTO.ReSearch.class, FastReSearchResponseDTO.ReSearch.class),
-        RECOMMENDATIONS("/ai/recommendations", FastHomeRequestDTO.HomeRecommendRequest.class,
+
+        // 추천
+        RECOMMENDATIONS("/api/quick-search/recommendations", FastHomeRequestDTO.HomeRecommendRequest.class,
+                        FastHomeResponseDTO.HomeRecommend.class), // 일반 추천
+        RECOMMENDATIONS_BY_MEMBER("/api/quick-search/recommendations/by-member",
+                        FastHomeRequestDTO.HomeRecommendByMemberRequest.class,
                         FastHomeResponseDTO.HomeRecommend.class),
         COMPARE("/ai/compare", FastLibraryRequestDTO.LibraryCompare.class,
                         FastLibraryCompareResponseDTO.CompareResult.class),
+
+        // 차트
+        CHART_RECOMMENDATIONS("/api/chart/search-result/{searchId}/recommendations", Void.class,
+                        FastChartResponseDTO.ChartRecommendationsResponse.class),
         // REFINE_SEARCH("/search/refine",
         // FastNaturalSearchResponseDTO.SearchResult.class),
         ;
diff --git a/src/main/java/DiffLens/back_end/global/fastapi/FastApiService.java b/src/main/java/DiffLens/back_end/global/fastapi/FastApiService.java
index 03c1ca0..c9e663f 100644
--- a/src/main/java/DiffLens/back_end/global/fastapi/FastApiService.java
+++ b/src/main/java/DiffLens/back_end/global/fastapi/FastApiService.java
@@ -8,6 +8,7 @@
 import DiffLens.back_end.global.fastapi.dto.response.FastNaturalLanguageResponseDTO;
 import DiffLens.back_end.global.fastapi.dto.response.FastLibraryCompareResponseDTO;
 import DiffLens.back_end.global.fastapi.dto.response.MainSearchResponse;
+import DiffLens.back_end.global.fastapi.dto.response.FastChartResponseDTO;
 import lombok.RequiredArgsConstructor;
 import org.springframework.stereotype.Service;
 
@@ -41,4 +42,13 @@ public FastHomeResponseDTO.HomeRecommend recommend(FastHomeRequestDTO.HomeRecomm
         return fastApiClient.sendRequest(FastApiRequestType.RECOMMENDATIONS, request);
     }
 
+    // 차트 추천
+    public FastChartResponseDTO.ChartRecommendationsResponse getChartRecommendations(Long searchId) {
+        return fastApiClient.sendRequestWithPathVariable(
+                FastApiRequestType.CHART_RECOMMENDATIONS,
+                null,
+                searchId
+        );
+    }
+
 }
diff --git a/src/main/java/DiffLens/back_end/global/fastapi/dto/request/FastHomeRequestDTO.java b/src/main/java/DiffLens/back_end/global/fastapi/dto/request/FastHomeRequestDTO.java
index ee726b0..7718409 100644
--- a/src/main/java/DiffLens/back_end/global/fastapi/dto/request/FastHomeRequestDTO.java
+++ b/src/main/java/DiffLens/back_end/global/fastapi/dto/request/FastHomeRequestDTO.java
@@ -1,9 +1,7 @@
 package DiffLens.back_end.global.fastapi.dto.request;
 
-import lombok.AllArgsConstructor;
-import lombok.Builder;
-import lombok.Getter;
-import lombok.NoArgsConstructor;
+import com.fasterxml.jackson.annotation.JsonProperty;
+import lombok.*;
 
 import java.util.List;
 
@@ -13,6 +11,7 @@
  * Spring Boot ->  Fast API 요청 형태
  *
  */
+@RequiredArgsConstructor
 public class FastHomeRequestDTO {
 
     @Getter
@@ -20,9 +19,36 @@ public class FastHomeRequestDTO {
     @NoArgsConstructor
     @AllArgsConstructor
     public static class HomeRecommendRequest {
-        private Long memberId;
-        private HomeRecommendOnboarding onboarding;
+
+        @JsonProperty("search_history")
         private List<String> recentSearches;
+
+        @JsonProperty("limit")
+        private Integer limit;
+
+        @JsonProperty("industry")
+        private String industry;
+
+    }
+
+    @Getter
+    @Builder
+    @NoArgsConstructor
+    @AllArgsConstructor
+    public static class HomeRecommendByMemberRequest {
+
+        @JsonProperty("member_id")
+        private Long memberId;
+
+        @JsonProperty("limit")
+        private Integer limit;
+
+        @JsonProperty("history_limit")
+        private Integer historyLimit;
+
+        @JsonProperty("industry")
+        private String industry;
+
     }
 
     @Getter
diff --git a/src/main/java/DiffLens/back_end/global/fastapi/dto/response/FastChartResponseDTO.java b/src/main/java/DiffLens/back_end/global/fastapi/dto/response/FastChartResponseDTO.java
new file mode 100644
index 0000000..39d18d6
--- /dev/null
+++ b/src/main/java/DiffLens/back_end/global/fastapi/dto/response/FastChartResponseDTO.java
@@ -0,0 +1,83 @@
+package DiffLens.back_end.global.fastapi.dto.response;
+
+import com.fasterxml.jackson.annotation.JsonProperty;
+import lombok.*;
+
+import java.util.List;
+import java.util.Map;
+
+/**
+ * FastAPI 차트 추천 응답 DTO
+ */
+public class FastChartResponseDTO {
+
+  @Getter
+  @Setter
+  @NoArgsConstructor
+  @AllArgsConstructor
+  @Builder
+  public static class ChartRecommendationsResponse {
+    @JsonProperty("search_id")
+    private Long searchId;
+
+    @JsonProperty("panel_count")
+    private Integer panelCount;
+
+    @JsonProperty("original_query")
+    private String originalQuery;
+
+    @JsonProperty("cohort_stats")
+    private Map<String, Map<String, Integer>> cohortStats;
+
+    @JsonProperty("main_chart")
+    private ChartData mainChart;
+
+    @JsonProperty("sub_charts")
+    private List<ChartData> subCharts;
+  }
+
+  @Getter
+  @Setter
+  @NoArgsConstructor
+  @AllArgsConstructor
+  @Builder
+  public static class ChartData {
+    @JsonProperty("chart_type")
+    private String chartType;
+
+    private String metric;
+
+    private String title;
+
+    private String reasoning;
+
+    private List<ChartDataPoint> data;
+  }
+
+  @Getter
+  @Setter
+  @NoArgsConstructor
+  @AllArgsConstructor
+  @Builder
+  public static class ChartDataPoint {
+    private String category;
+
+    private Integer value;
+
+    // stacked-bar, infographic 차트용 추가 필드들
+    private Integer male;
+
+    @JsonProperty("male_max")
+    private Integer maleMax;
+
+    private Integer female;
+
+    @JsonProperty("female_max")
+    private Integer femaleMax;
+
+    // map 차트용
+    private String id;
+
+    private String name;
+  }
+}
diff --git a/src/main/java/DiffLens/back_end/global/fastapi/dto/response/FastHomeResponseDTO.java b/src/main/java/DiffLens/back_end/global/fastapi/dto/response/FastHomeResponseDTO.java
index 07266da..423c370 100644
--- a/src/main/java/DiffLens/back_end/global/fastapi/dto/response/FastHomeResponseDTO.java
+++ b/src/main/java/DiffLens/back_end/global/fastapi/dto/response/FastHomeResponseDTO.java
@@ -1,8 +1,7 @@
 package DiffLens.back_end.global.fastapi.dto.response;
 
-import lombok.Builder;
-import lombok.Getter;
-import lombok.Setter;
+import com.fasterxml.jackson.annotation.JsonProperty;
+import lombok.*;
 
 import java.util.List;
 
@@ -10,40 +9,118 @@ public class FastHomeResponseDTO {
 
     @Getter
     @Builder
+    @AllArgsConstructor
+    @NoArgsConstructor
     public static class HomeRecommend{
 
-        private Boolean success;
-        private Data data;
+        @JsonProperty("recommendations")
+        private List<Recommendation> recommendations;
 
-    }
+        @JsonProperty("strategy_used")
+        private String strategyUsed;
 
-    @Getter
-    @Setter
-    public static class Data{
-        private List<Recommendation> recommendations;
+        @JsonProperty("total_count")
+        private int totalCount;
+
+        @JsonProperty("patterns")
+        private Object patterns;
     }
 
     @Getter
-    @Setter
-    public static class Recommendation{
+    @Builder
+    @NoArgsConstructor
+    @AllArgsConstructor
+    public static class Recommendation {
+
+        @JsonProperty("id")
         private Long id;
-        private String title;
-        private String description;
-        private String icon;
+
+        @JsonProperty("query")
         private String query;
-        private RecommendationFilter filters;
+
+        @JsonProperty("count")
+        private String count;
+
+        @JsonProperty("description")
+        private String description;
+
+        @JsonProperty("category")
+        private String category;
+
+        @JsonProperty("personalized")
+        private Boolean personalized;
+
+        @JsonProperty("search_params")
+        private Object searchParams;
+
+        @JsonProperty("recommended_mode")
+        private String recommendedMode;
     }
 
     @Getter
-    @Setter
-    public static class RecommendationFilter{
-        private String respondentCount;
-        private List<String> region;
-        private List<String> occupation;
+    @Builder
+    @NoArgsConstructor
+    @AllArgsConstructor
+    public static class SearchParams {
+
+        @JsonProperty("age_group")
+        private String ageGroup;
+
+        @JsonProperty("gender")
         private String gender;
-        private String martialStatus;
-        private String reason;
+
+        @JsonProperty("region")
+        private String region;
+
+        @JsonProperty("marital_status")
+        private String maritalStatus;
+
+        @JsonProperty("occupation")
+        private List<String> occupation;
+
+        @JsonProperty("brands")
+        private List<String> brands;
+
+        @JsonProperty("limit")
+        private int limit;
     }
 
+    @Getter
+    @Builder
+    @NoArgsConstructor
+    @AllArgsConstructor
+    public static class Patterns {
+
+        @JsonProperty("demographic")
+        private Demographic demographic;
 
+        @JsonProperty("survey_consumption")
+        private SurveyConsumption surveyConsumption;
+    }
+
+    @Getter
+    @Builder
+    @NoArgsConstructor
+    @AllArgsConstructor
+    public static class Demographic {
+
+        @JsonProperty("연령대")
+        private List<String> 연령대;
+
+        @JsonProperty("성별")
+        private List<String> 성별;
+
+        @JsonProperty("거주지역")
+        private List<String> 거주지역;
+    }
+
+    @Getter
+    @Builder
+    @NoArgsConstructor
+    @AllArgsConstructor
+    public static class SurveyConsumption {
+
+        @JsonProperty("OTT개수")
+        private List<String> ott개수;
+    }
 }
diff --git a/src/main/java/DiffLens/back_end/global/fastapi/dto/response/MainSearchResponse.java b/src/main/java/DiffLens/back_end/global/fastapi/dto/response/MainSearchResponse.java
index 1de14dd..5b8fb5b 100644
--- a/src/main/java/DiffLens/back_end/global/fastapi/dto/response/MainSearchResponse.java
+++ b/src/main/java/DiffLens/back_end/global/fastapi/dto/response/MainSearchResponse.java
@@ -7,6 +7,7 @@
 import java.util.List;
 import java.util.Map;
 
+@ToString
 @Getter
 @Setter
 @NoArgsConstructor
@@ -68,6 +69,9 @@ public static class PanelInfo {
 
         @Schema(description = "해시태그 목록")
         private List<String> hashtags;
+
+        @JsonProperty("similarity")
+        private Double similarity;
     }
 
 }
diff --git a/src/main/java/DiffLens/back_end/global/redis/CacheService.java b/src/main/java/DiffLens/back_end/global/redis/CacheService.java
new file mode 100644
index 0000000..3d44f50
--- /dev/null
+++ b/src/main/java/DiffLens/back_end/global/redis/CacheService.java
@@ -0,0 +1,17 @@
+package DiffLens.back_end.global.redis;
+
+/**
+ *
+ * Redis 에서 캐시를 다루는 서비스들의 공통 인터페이스
+ *
+ * @param <T> Redis에서 캐시로 다룰 데이터
+ * @param <R> 캐시를 저장하거나 찾는 데에 사용할 데이터
+ */
+public interface CacheService <T, R>{
+
+    T getCacheInfo(R key);
+
+    void saveCacheInfo(R data, T cacheInfo);
+
+
+}