diff --git a/concrete/numpy/tracing.py b/concrete/numpy/tracing.py
index 4af5fd446..5cd78bc4f 100644
--- a/concrete/numpy/tracing.py
+++ b/concrete/numpy/tracing.py
@@ -7,7 +7,7 @@ import numpy
 from numpy.typing import DTypeLike
 
 from ..common.data_types.dtypes_helpers import mix_values_determine_holding_dtype
-from ..common.debugging.custom_assert import custom_assert
+from ..common.debugging.custom_assert import assert_true, custom_assert
 from ..common.operator_graph import OPGraph
 from ..common.representation.intermediate import ArbitraryFunction, Constant, Dot
 from ..common.tracing import BaseTracer, make_input_tracers, prepare_function_parameters
@@ -53,7 +53,7 @@ class NPTracer(BaseTracer):
         raise NotImplementedError("Only __call__ method is supported currently")
 
     def __array_function__(self, func, _types, args, kwargs):
-        """Catch calls to numpy function in routes them to hnp functions if supported.
+        """Catch calls to numpy function in routes them to tracing functions if supported.
 
         Read more: https://numpy.org/doc/stable/user/basics.dispatch.html#basics-dispatch
         """
@@ -62,7 +62,8 @@ class NPTracer(BaseTracer):
             (len(kwargs) == 0),
             f"**kwargs are currently not supported for numpy functions, func: {func}",
         )
-        return tracing_func(*args, **kwargs)
+        sanitized_args = [self._sanitize(arg) for arg in args]
+        return tracing_func(self, *sanitized_args, **kwargs)
 
     def astype(self, numpy_dtype: DTypeLike, *args, **kwargs) -> "NPTracer":
         r"""Support numpy astype feature.
@@ -222,26 +223,25 @@ class NPTracer(BaseTracer):
         )
         return output_tracer
 
-    def dot(self, other_tracer: "NPTracer", **_kwargs) -> "NPTracer":
+    def dot(self, *args: "NPTracer", **_kwargs) -> "NPTracer":
         """Trace numpy.dot.
 
         Returns:
             NPTracer: The output NPTracer containing the traced function
         """
-        # input_tracers contains the other tracer of the dot product
-        dot_inputs = (self, self._sanitize(other_tracer))
+        assert_true((num_args := len(args)) == 2, f"dot expects 2 inputs got {num_args}")
 
-        common_output_dtypes = self._manage_dtypes(numpy.dot, *dot_inputs)
+        common_output_dtypes = self._manage_dtypes(numpy.dot, *args)
         custom_assert(len(common_output_dtypes) == 1)
 
         traced_computation = Dot(
-            [input_tracer.output for input_tracer in dot_inputs],
+            [input_tracer.output for input_tracer in args],
             common_output_dtypes[0],
             delegate_evaluation_function=numpy.dot,
         )
 
         output_tracer = self.__class__(
-            dot_inputs,
+            args,
             traced_computation=traced_computation,
             output_index=0,
         )