diff --git a/source/use_case/kws/src/UseCaseHandler.cc b/source/use_case/kws/src/UseCaseHandler.cc
index 872d323..d2cba55 100644
--- a/source/use_case/kws/src/UseCaseHandler.cc
+++ b/source/use_case/kws/src/UseCaseHandler.cc
@@ -82,6 +82,7 @@
     bool ClassifyAudioHandler(ApplicationContext& ctx, uint32_t clipIndex, bool runAll)
     {
         auto& platform = ctx.Get<hal_platform&>("platform");
+        auto& profiler = ctx.Get<Profiler&>("profiler");
 
         constexpr uint32_t dataPsnTxtInfStartX = 20;
         constexpr uint32_t dataPsnTxtInfStartY = 40;
@@ -215,7 +216,7 @@
                      audioDataSlider.TotalStrides() + 1);
 
                 /* Run inference over this audio clip sliding window. */
-                arm::app::RunInference(platform, model);
+                arm::app::RunInference(model, profiler);
 
                 std::vector<ClassificationResult> classificationResult;
                 auto& classifier = ctx.Get<KwsClassifier&>("classifier");
@@ -243,6 +244,8 @@
                 return false;
             }
 
+            profiler.PrintProfilingResult();
+
             _IncrementAppCtxClipIdx(ctx);
 
         } while (runAll && ctx.Get<uint32_t>("clipIndex") != startClipIdx);
@@ -281,6 +284,8 @@
         constexpr uint32_t dataPsnTxtYIncr   = 16;  /* Row index increment. */
 
         platform.data_psn->set_text_color(COLOR_GREEN);
+        info("Final results:\n");
+        info("Total number of inferences: %zu\n", results.size());
 
         /* Display each result */
         uint32_t rowIdx1 = dataPsnTxtStartY1 + 2 * dataPsnTxtYIncr;
@@ -290,7 +295,7 @@
             std::string topKeyword{"<none>"};
             float score = 0.f;
 
-            if (results[i].m_resultVec.size()) {
+            if (!results[i].m_resultVec.empty()) {
                 topKeyword = results[i].m_resultVec[0].m_label;
                 score = results[i].m_resultVec[0].m_normalisedVal;
             }
@@ -305,13 +310,20 @@
                                     dataPsnTxtStartX1, rowIdx1, false);
             rowIdx1 += dataPsnTxtYIncr;
 
-            info("For timestamp: %f (inference #: %u); threshold: %f\n",
-                    results[i].m_timeStamp, results[i].m_inferenceNumber,
-                    results[i].m_threshold);
-            for (uint32_t j = 0; j < results[i].m_resultVec.size(); ++j) {
-                info("\t\tlabel @ %u: %s, score: %f\n", j,
-                    results[i].m_resultVec[j].m_label.c_str(),
-                    results[i].m_resultVec[j].m_normalisedVal);
+            if (results[i].m_resultVec.empty()) {
+                info("For timestamp: %f (inference #: %u); label: %s; threshold: %f\n",
+                     results[i].m_timeStamp, results[i].m_inferenceNumber,
+                     topKeyword.c_str(),
+                     results[i].m_threshold);
+            } else {
+                for (uint32_t j = 0; j < results[i].m_resultVec.size(); ++j) {
+                    info("For timestamp: %f (inference #: %u); label: %s, score: %f; threshold: %f\n",
+                         results[i].m_timeStamp,
+                         results[i].m_inferenceNumber,
+                         results[i].m_resultVec[j].m_label.c_str(),
+                         results[i].m_resultVec[j].m_normalisedVal,
+                         results[i].m_threshold);
+                }
             }
         }