diff --git a/src/birdnetlib/analyzer.py b/src/birdnetlib/analyzer.py
index 16716fb..ece315c 100644
--- a/src/birdnetlib/analyzer.py
+++ b/src/birdnetlib/analyzer.py
@@ -53,6 +53,7 @@ def __init__(
         custom_species_list=None,
         classifier_model_path=None,
         classifier_labels_path=None,
+        fetch_embeddings=None,
     ):
         self.name = "Analyzer"
         self.model_name = "BirdNET-Analyzer"
@@ -71,7 +72,12 @@ def __init__(
         self.labels = []
         self.results = []
         self.custom_species_list = []
-
+        
+        if fetch_embeddings:
+            self.fetch_embeddings = True
+        else:
+            self.fetch_embeddings = False
+        
         self.classifier_model_path = classifier_model_path
         self.classifier_labels_path = classifier_labels_path
         self.use_custom_classifier = (
@@ -200,10 +206,15 @@ def analyze_recording(self, recording):
         start = 0
         end = recording.sample_secs
         results = {}
+        features = []
         for c in recording.chunks:
 
             if self.use_custom_classifier:
                 pred = self.predict_with_custom_classifier(c)[0]
+            elif self.fetch_embeddings == True:
+            	feature = self.predict_with_custom_classifier(c)
+            	features.append(feature)
+            	continue
             else:
                 pred = self.predict(c)[0]
 
@@ -226,7 +237,9 @@ def analyze_recording(self, recording):
             end = start + recording.sample_secs
 
         self.results = results
+        self.features_list = features
         recording.detection_list = self.detections
+        recording.features_list = self.features_list
 
     def load_model(self):
         print("load model", not self.use_custom_classifier)
@@ -246,7 +259,7 @@ def load_model(self):
         self.input_layer_index = self.input_details[0]["index"]
 
         # Get classification output or feature embeddings
-        if self.use_custom_classifier:
+        if self.use_custom_classifier or self.fetch_embeddings:
             self.output_layer_index = self.output_details[0]["index"] - 1
         else:
             self.output_layer_index = self.output_details[0]["index"]
@@ -299,7 +312,9 @@ def predict_with_custom_classifier(self, sample):
         features = INTERPRETER.get_tensor(OUTPUT_LAYER_INDEX)
 
         feature_vector = features
-
+        if self.fetch_embeddings:
+            return feature_vector
+            
         C_INTERPRETER = self.custom_interpreter
         C_INPUT_LAYER_INDEX = self.custom_input_layer_index
         C_OUTPUT_LAYER_INDEX = self.custom_output_layer_index
diff --git a/src/birdnetlib/main.py b/src/birdnetlib/main.py
index 338e647..e5bb7a9 100644
--- a/src/birdnetlib/main.py
+++ b/src/birdnetlib/main.py
@@ -29,6 +29,7 @@ def __init__(
         self.analyzer = analyzer
         self.detections_dict = {}  # Old format
         self.detection_list = []
+        self.features_list = []
         self.analyzed = False
         self.week_48 = week_48
         self.date = date
@@ -94,6 +95,9 @@ def detections(self):
                 qualified_detections.append(detection)
 
         return qualified_detections
+    @property
+    def features(self):
+    	return self.features_list
 
     @property
     def as_dict(self):
@@ -299,4 +303,4 @@ def as_dict(self):
 
 
 if __name__ == "__main__":
-    pass
\ No newline at end of file
+    pass