diff --git a/kmath-multik/src/main/kotlin/space/kscience/kmath/multik/MultikTensorAlgebra.kt b/kmath-multik/src/main/kotlin/space/kscience/kmath/multik/MultikTensorAlgebra.kt
index c229a44bf..ed5575b93 100644
--- a/kmath-multik/src/main/kotlin/space/kscience/kmath/multik/MultikTensorAlgebra.kt
+++ b/kmath-multik/src/main/kotlin/space/kscience/kmath/multik/MultikTensorAlgebra.kt
@@ -3,9 +3,14 @@
  * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file.
  */
 
+@file:Suppress("unused")
+
 package space.kscience.kmath.multik
 
+import org.jetbrains.kotlinx.multik.api.Multik
+import org.jetbrains.kotlinx.multik.api.linalg.dot
 import org.jetbrains.kotlinx.multik.api.mk
+import org.jetbrains.kotlinx.multik.api.ndarrayOf
 import org.jetbrains.kotlinx.multik.api.zeros
 import org.jetbrains.kotlinx.multik.ndarray.data.*
 import org.jetbrains.kotlinx.multik.ndarray.operations.*
@@ -30,8 +35,20 @@ public value class MultikTensor<T>(public val array: MutableMultiArray<T, DN>) :
     }
 }
 
+private fun <T, D : Dimension> MultiArray<T, D>.asD1Array(): D1Array<T> {
+    if (this is NDArray<T, D>)
+        return this.asD1Array()
+    else throw ClassCastException("Cannot cast MultiArray to NDArray.")
+}
 
-public class MultikTensorAlgebra<T> internal constructor(
+
+private fun <T, D : Dimension> MultiArray<T, D>.asD2Array(): D2Array<T> {
+    if (this is NDArray<T, D>)
+        return this.asD2Array()
+    else throw ClassCastException("Cannot cast MultiArray to NDArray.")
+}
+
+public class MultikTensorAlgebra<T : Number> internal constructor(
     public val type: DataType,
     public val elementAlgebra: Ring<T>,
     public val comparator: Comparator<T>
@@ -162,9 +179,18 @@ public class MultikTensorAlgebra<T> internal constructor(
 
     override fun Tensor<T>.viewAs(other: Tensor<T>): MultikTensor<T> = view(other.shape)
 
-    override fun Tensor<T>.dot(other: Tensor<T>): MultikTensor<T> {
-        TODO("Not yet implemented")
-    }
+    override fun Tensor<T>.dot(other: Tensor<T>): MultikTensor<T> =
+        if (this.shape.size == 1 && other.shape.size == 1) {
+            Multik.ndarrayOf(
+                asMultik().array.asD1Array() dot other.asMultik().array.asD1Array()
+            ).asDNArray().wrap()
+        } else if (this.shape.size == 2 && other.shape.size == 2) {
+            (asMultik().array.asD2Array() dot other.asMultik().array.asD2Array()).asDNArray().wrap()
+        } else if(this.shape.size == 2 && other.shape.size == 1) {
+            (asMultik().array.asD2Array() dot other.asMultik().array.asD1Array()).asDNArray().wrap()
+        } else {
+            TODO("Not implemented for broadcasting")
+        }
 
     override fun diagonalEmbedding(diagonalEntries: Tensor<T>, offset: Int, dim1: Int, dim2: Int): MultikTensor<T> {
         TODO("Diagonal embedding not implemented")