diff --git a/source/application/api/use_case/kws/include/KwsClassifier.hpp b/source/application/api/use_case/kws/include/KwsClassifier.hpp
new file mode 100644
index 0000000..d050e85
--- /dev/null
+++ b/source/application/api/use_case/kws/include/KwsClassifier.hpp
@@ -0,0 +1,66 @@
+/*
+ * Copyright (c) 2022 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#ifndef KWS_CLASSIFIER_HPP
+#define KWS_CLASSIFIER_HPP
+
+#include "ClassificationResult.hpp"
+#include "TensorFlowLiteMicro.hpp"
+#include "Classifier.hpp"
+
+#include <vector>
+
+namespace arm {
+namespace app {
+
+    /**
+     * @brief   KWS Classifier - a helper class to get certain number of top
+     *          results from the output vector from a classification NN.
+     *          Allows for averaging of previous results.
+     **/
+    class KwsClassifier : public Classifier {
+    public:
+
+        /**
+         * @brief           Gets the top N classification results from the
+         *                  output vector.
+         * @param[in]       outputTensor   Inference output tensor from an NN model.
+         * @param[out]      vecResults     A vector of classification results.
+         *                                 populated by this function.
+         * @param[in]       labels         Labels vector to match classified classes.
+         * @param[in]       topNCount      Number of top classifications to pick. Default is 1.
+         * @param[in]       useSoftmax     Whether Softmax normalisation should be applied to output. Default is false.
+         * @param[in/out]   resultHistory  History of previous classification results to be updated.
+         * @return          true if successful, false otherwise.
+         **/
+         using Classifier::GetClassificationResults;  /* We are overloading not overriding. */
+         bool GetClassificationResults(TfLiteTensor* outputTensor, std::vector<ClassificationResult>& vecResults,
+                 const std::vector <std::string>& labels, uint32_t topNCount,
+                 bool use_softmax, std::vector<std::vector<float>>& resultHistory);
+
+        /**
+         * @brief        Average the given history of results.
+         * @param[in]    resultHistory   The history of results to take on average of.
+         * @param[out]   averageResult   The calculated average.
+         **/
+         static void AveragResults(const std::vector<std::vector<float>>& resultHistory,
+                 std::vector<float>& averageResult);
+    };
+
+} /* namespace app */
+} /* namespace arm */
+
+#endif /* KWS_CLASSIFIER_HPP */