diff --git a/storage.go b/storage.go
new file mode 100644
index 0000000..9bac442
--- /dev/null
+++ b/storage.go
@@ -0,0 +1,138 @@
+package nn
+
+import (
+	"encoding/json"
+	"fmt"
+	"gonum.org/v1/gonum/mat"
+	"io"
+	"io/ioutil"
+)
+
+type jsonNetwork struct {
+	Layers  []uint      `json:"layers"`
+	Biases  [][]float64 `json:"biases"`
+	Weights [][]float64 `json:"weights"`
+}
+
+// MarshallJSON implements the json.Marshaler interface
+func (net *Network) MarshalJSON() ([]byte, error) {
+
+	raw := new(jsonNetwork)
+
+	// 1. Layers
+	raw.Layers = net.layers
+
+	// 2. Biases
+	raw.Biases = make([][]float64, 0)
+	for _, bias := range net.Biases {
+
+		vector := bias.ColView(0)
+		biasJSON := make([]float64, 0)
+
+		for i, l := 0, vector.Len(); i < l; i++ {
+			biasJSON = append(biasJSON, vector.AtVec(i))
+		}
+
+		raw.Biases = append(raw.Biases, biasJSON)
+	}
+
+	// 3. Weights
+	raw.Weights = make([][]float64, 0)
+	for _, weight := range net.Weights {
+
+		rows, cols := weight.Dims()
+		weightJSON := make([]float64, 0)
+
+		for row := 0; row < rows; row++ {
+			for col := 0; col < cols; col++ {
+				weightJSON = append(weightJSON, weight.At(row, col))
+			}
+		}
+
+		raw.Weights = append(raw.Weights, weightJSON)
+	}
+
+	return json.Marshal(raw)
+
+}
+
+// UnmarshalJSON implements the json.Unmarshaler interface
+func (net *Network) UnmarshalJSON(in []byte) error {
+
+	// parse as 'jsonNetwork' struct
+	raw := new(jsonNetwork)
+	err := json.Unmarshal(in, raw)
+	if err != nil {
+		return err
+	}
+
+	net.fed = false
+	net.layers = raw.Layers
+
+	// extract biases
+	net.Biases = make([]*mat.Dense, 0)
+	for l, layer := range net.layers {
+		if l == 0 {
+			continue
+		}
+		net.Biases = append(net.Biases, mat.NewDense(int(layer), 1, raw.Biases[l-1]))
+	}
+	// extract weights
+	net.Weights = make([]*mat.Dense, 0)
+	for l, layer := range net.layers {
+		if l == 0 {
+			continue
+		}
+		net.Weights = append(net.Weights, mat.NewDense(int(layer), int(net.layers[l-1]), raw.Weights[l-1]))
+	}
+
+	// mockup neurons
+	net.Neurons = make([]*mat.Dense, 0)
+	for _, layer := range net.layers {
+		net.Neurons = append(net.Neurons, mat.NewDense(int(layer), 1, nil))
+	}
+	fmt.Printf("neurons: %v\n", net.Neurons)
+
+	// extract into the current network receiver (net)
+	return nil
+}
+
+// WriteTo implements the io.WriterTo interface
+func (net *Network) WriteTo(w io.Writer) (int64, error) {
+
+	// get json
+	raw, err := json.Marshal(net)
+	if err != nil {
+		return 0, nil
+	}
+
+	// write to file
+	written, err := w.Write(raw)
+	return int64(written), err
+}
+
+// ReadFrom implements the io.ReaderFrom interface
+func (net *Network) ReadFrom(r io.Reader) (int64, error) {
+
+	// read
+	raw, err := ioutil.ReadAll(r)
+	if err != nil {
+		return 0, err
+	}
+
+	// parse json
+	readNet := new(Network)
+	err = json.Unmarshal(raw, readNet)
+	if err != nil {
+		return 0, err
+	}
+
+	// copy values
+	net.layers = readNet.layers
+	net.fed = readNet.fed
+	net.Neurons = readNet.Neurons
+	net.Biases = readNet.Biases
+	net.Weights = readNet.Weights
+
+	return int64(len(raw)), nil
+}