diff --git a/src/blosc2/__init__.py b/src/blosc2/__init__.py
index 12a2a908..c820e199 100644
--- a/src/blosc2/__init__.py
+++ b/src/blosc2/__init__.py
@@ -433,6 +433,8 @@ def _raise(exc):
     full_like,
     save,
     stack,
+    cumulative_sum,
+    cumulative_prod,
 )
 from .embed_store import EmbedStore, estore_from_cframe
 from .dict_store import DictStore
diff --git a/src/blosc2/ndarray.py b/src/blosc2/ndarray.py
index 3a33c54c..00b2def6 100644
--- a/src/blosc2/ndarray.py
+++ b/src/blosc2/ndarray.py
@@ -6370,3 +6370,69 @@ def mygen(i):
     for a in myarrs:
         out += (broadcast_to(a, shape),)
     return out
+
+
+def cumulative_sum(x, /, *, axis=None, dtype=None, include_initial=False):
+    """Array API cumulative_sum.
+
+    Parameters
+    ----------
+    x : array-like or NDArray
+        Input array.
+    axis : int or None
+        Axis along which to compute the cumulative sum. For ndim > 1, this
+        must be provided. Default: None (flatten).
+    dtype : dtype or None
+        Accumulator/output dtype. If None, follow type-promotion rules.
+    include_initial : bool, default False
+        If True, include the additive identity (zero) as the first value along
+        the reduced axis (output length N+1).
+
+    Returns
+    -------
+    NDArray
+        Array containing the cumulative sums.
+    """
+    # Accept blosc2.NDArray or array-like
+    if isinstance(x, NDArray):
+        arr = x[:]  # read into NumPy array
+    else:
+        arr = np.asarray(x)
+
+    # Use NumPy's Array API compatible cumulative_sum function
+    res = np.cumulative_sum(arr, axis=axis, dtype=dtype, include_initial=include_initial)
+
+    return blosc2.asarray(res)
+
+
+def cumulative_prod(x, /, *, axis=None, dtype=None, include_initial=False):
+    """Array API cumulative_prod.
+
+    Parameters
+    ----------
+    x : array-like or NDArray
+        Input array.
+    axis : int or None
+        Axis along which to compute the cumulative product. For ndim > 1, this
+        must be provided. Default: None (flatten).
+    dtype : dtype or None
+        Accumulator/output dtype. If None, follow type-promotion rules.
+    include_initial : bool, default False
+        If True, include the multiplicative identity (one) as the first value along
+        the reduced axis (output length N+1).
+
+    Returns
+    -------
+    NDArray
+        Array containing the cumulative products.
+    """
+    # Accept blosc2.NDArray or array-like
+    if isinstance(x, NDArray):
+        arr = x[:]  # read into NumPy array
+    else:
+        arr = np.asarray(x)
+
+    # Use NumPy's Array API compatible cumulative_prod function
+    res = np.cumulative_prod(arr, axis=axis, dtype=dtype, include_initial=include_initial)
+
+    return blosc2.asarray(res)