diff --git a/NDTensors/src/lib/GradedAxes/src/unitrangedual.jl b/NDTensors/src/lib/GradedAxes/src/unitrangedual.jl
index 3ce65a4d15..8f1a86f1b8 100644
--- a/NDTensors/src/lib/GradedAxes/src/unitrangedual.jl
+++ b/NDTensors/src/lib/GradedAxes/src/unitrangedual.jl
@@ -38,6 +38,11 @@ function unitrangedual_getindices_blocks(a, indices)
   return mortar([dual(b) for b in blocks(a_indices)])
 end
 
+# TODO: Move this to a `BlockArraysExtensions` library.
+function blockedunitrange_getindices(a::UnitRangeDual, indices::Block{1})
+  return a[indices]
+end
+
 function Base.getindex(a::UnitRangeDual, indices::Vector{<:Block{1}})
   return unitrangedual_getindices_blocks(a, indices)
 end
diff --git a/NDTensors/src/lib/LabelledNumbers/src/labelledinteger.jl b/NDTensors/src/lib/LabelledNumbers/src/labelledinteger.jl
index f5e2d58f3d..323d252b0c 100644
--- a/NDTensors/src/lib/LabelledNumbers/src/labelledinteger.jl
+++ b/NDTensors/src/lib/LabelledNumbers/src/labelledinteger.jl
@@ -86,3 +86,32 @@ Base.:-(x::LabelledInteger) = labelled_minus(x)
 # TODO: This is only needed for older Julia versions, like Julia 1.6.
 # Delete once we drop support for older Julia versions.
 Base.hash(x::LabelledInteger, h::UInt64) = labelled_hash(x, h)
+
+using Random: AbstractRNG, default_rng
+default_eltype() = Float64
+for f in [:rand, :randn]
+  @eval begin
+    function Base.$f(
+      rng::AbstractRNG,
+      elt::Type{<:Number},
+      dims::Tuple{LabelledInteger,Vararg{LabelledInteger}},
+    )
+      return a = $f(rng, elt, unlabel.(dims))
+    end
+    function Base.$f(
+      rng::AbstractRNG,
+      elt::Type{<:Number},
+      dim1::LabelledInteger,
+      dims::Vararg{LabelledInteger},
+    )
+      return $f(rng, elt, (dim1, dims...))
+    end
+    Base.$f(elt::Type{<:Number}, dims::Tuple{LabelledInteger,Vararg{LabelledInteger}}) =
+      $f(default_rng(), elt, dims)
+    Base.$f(elt::Type{<:Number}, dim1::LabelledInteger, dims::Vararg{LabelledInteger}) =
+      $f(elt, (dim1, dims...))
+    Base.$f(dims::Tuple{LabelledInteger,Vararg{LabelledInteger}}) =
+      $f(default_eltype(), dims)
+    Base.$f(dim1::LabelledInteger, dims::Vararg{LabelledInteger}) = $f((dim1, dims...))
+  end
+end
diff --git a/NDTensors/src/lib/LabelledNumbers/test/runtests.jl b/NDTensors/src/lib/LabelledNumbers/test/runtests.jl
index cf3f87e86d..6fc1ac4231 100644
--- a/NDTensors/src/lib/LabelledNumbers/test/runtests.jl
+++ b/NDTensors/src/lib/LabelledNumbers/test/runtests.jl
@@ -1,4 +1,5 @@
 @eval module $(gensym())
+using LinearAlgebra: norm
 using NDTensors.LabelledNumbers: LabelledInteger, islabelled, label, labelled, unlabel
 using Test: @test, @testset
 @testset "LabelledNumbers" begin
@@ -48,6 +49,29 @@ using Test: @test, @testset
     @test one(typeof(x)) == true
     @test !islabelled(one(typeof(x)))
   end
+  @testset "randn" begin
+    d = labelled(2, "x")
+
+    a = randn(Float32, d, d)
+    @test eltype(a) === Float32
+    @test size(a) == (2, 2)
+    @test norm(a) > 0
+
+    a = rand(Float32, d, d)
+    @test eltype(a) === Float32
+    @test size(a) == (2, 2)
+    @test norm(a) > 0
+
+    a = randn(d, d)
+    @test eltype(a) === Float64
+    @test size(a) == (2, 2)
+    @test norm(a) > 0
+
+    a = rand(d, d)
+    @test eltype(a) === Float64
+    @test size(a) == (2, 2)
+    @test norm(a) > 0
+  end
   @testset "Labelled array ($a)" for a in (collect(2:5), 2:5)
     x = labelled(a, "x")
     @test eltype(x) == LabelledInteger{Int,String}