diff --git a/examples/async-clients/client/entrypoint.py b/examples/async-clients/client/entrypoint.py
deleted file mode 100644
index 0b8e10668..000000000
--- a/examples/async-clients/client/entrypoint.py
+++ /dev/null
@@ -1,135 +0,0 @@
-# /bin/python
-import fire
-import numpy as np
-from sklearn.datasets import make_classification
-from sklearn.metrics import accuracy_score
-from sklearn.model_selection import train_test_split
-from sklearn.neural_network import MLPClassifier
-
-from fedn.utils.helpers.helpers import get_helper, save_metadata, save_metrics
-
-HELPER_MODULE = "numpyhelper"
-ARRAY_SIZE = 10000
-
-
-def compile_model(max_iter=1):
-    clf = MLPClassifier(max_iter=max_iter)
-    # This is needed to initialize some state variables needed to make predictions
-    # We will overwrite weights and biases during FL training
-    X_train, y_train, _, _ = make_data()
-    clf.fit(X_train, y_train)
-    return clf
-
-
-def save_parameters(model, out_path):
-    """Save model to disk.
-
-    :param model: The model to save.
-    :type model: torch.nn.Module
-    :param out_path: The path to save to.
-    :type out_path: str
-    """
-    helper = get_helper(HELPER_MODULE)
-    parameters = model.coefs_ + model.intercepts_
-
-    helper.save(parameters, out_path)
-
-
-def load_parameters(model_path):
-    """Load model from disk.
-
-    param model_path: The path to load from.
-    :type model_path: str
-    :return: The loaded model.
-    :rtype: torch.nn.Module
-    """
-    helper = get_helper(HELPER_MODULE)
-    parameters = helper.load(model_path)
-
-    return parameters
-
-
-def init_seed(out_path="seed.npz"):
-    """Initialize seed model.
-
-    :param out_path: The path to save the seed model to.
-    :type out_path: str
-    """
-    # Init and save
-    model = compile_model()
-    save_parameters(model, out_path)
-
-
-def make_data(n_min=50, n_max=100):
-    """Generate / simulate a random number n data points.
-
-    n will fall in the interval (n_min, n_max)
-
-    """
-    n_samples = 100000
-    X, y = make_classification(n_samples=n_samples, n_features=4, n_informative=4, n_redundant=0, random_state=42)
-    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
-
-    n = np.random.randint(n_min, n_max, 1)[0]
-    ind = np.random.choice(len(X_train), n)
-    X_train = X_train[ind, :]
-    y_train = y_train[ind]
-    return X_train, y_train, X_test, y_test
-
-
-def train(in_model_path, out_model_path):
-    """Train model."""
-    # Load model
-    parameters = load_parameters(in_model_path)
-    model = compile_model()
-    n = len(parameters) // 2
-    model.coefs_ = parameters[:n]
-    model.intercepts_ = parameters[n:]
-
-    # Train
-    X_train, y_train, _, _ = make_data()
-    epochs = 10
-    for i in range(epochs):
-        model.partial_fit(X_train, y_train)
-
-    # Metadata needed for aggregation server side
-    metadata = {
-        "num_examples": len(X_train),
-    }
-
-    # Save JSON metadata file
-    save_metadata(metadata, out_model_path)
-
-    # Save model update
-    save_parameters(model, out_model_path)
-
-
-def validate(in_model_path, out_json_path):
-    """Validate model.
-
-    :param in_model_path: The path to the input model.
-    :type in_model_path: str
-    :param out_json_path: The path to save the output JSON to.
-    :type out_json_path: str
-    :param data_path: The path to the data file.
-    :type data_path: str
-    """
-    parameters = load_parameters(in_model_path)
-    model = compile_model()
-    n = len(parameters) // 2
-    model.coefs_ = parameters[:n]
-    model.intercepts_ = parameters[n:]
-
-    X_train, y_train, X_test, y_test = make_data()
-
-    # JSON schema
-    report = {
-        "accuracy_score": accuracy_score(y_test, model.predict(X_test)),
-    }
-
-    # Save JSON
-    save_metrics(report, out_json_path)
-
-
-if __name__ == "__main__":
-    fire.Fire({"init_seed": init_seed, "train": train, "validate": validate})
diff --git a/examples/async-clients/client/fedn.yaml b/examples/async-clients/client/fedn.yaml
deleted file mode 100644
index 1b08e4c81..000000000
--- a/examples/async-clients/client/fedn.yaml
+++ /dev/null
@@ -1,7 +0,0 @@
-entry_points:
-  build:
-    command: python entrypoint.py init_seed ../seed.npz
-  train:
-    command: python entrypoint.py train
-  validate: 
-    command: python entrypoint.py validate
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