diff --git a/.github/workflows/deploy-jupyterlite.yml b/.github/workflows/deploy-jupyterlite.yml
new file mode 100644
index 000000000..227ab1ea2
--- /dev/null
+++ b/.github/workflows/deploy-jupyterlite.yml
@@ -0,0 +1,64 @@
+name: Jupyterlite deployment
+
+on:
+  workflow_dispatch:
+  pull_request:
+    paths:
+      # Since we do not deploy in PRs and that this is only copying file from the repo
+      # the CI file is the only relevant change to watch for in CI on PRs
+      - .github/workflows/deploy-jupyterlite.yml
+  push:
+    branches:
+    - master
+
+permissions:
+  contents: read
+  pages: write
+  id-token: write
+
+jobs:
+  build:
+    runs-on: ubuntu-24.04
+    steps:
+    - name: Checkout code
+      uses: actions/checkout@v6
+    - uses: mamba-org/setup-micromamba@v3
+      with:
+        cache-environment: true
+        post-cleanup: 'all'
+        environment-name: jupyterlite-builder
+        create-args: jupyter jupyterlite-core jupyterlite-xeus
+    - name: Build WASM environment
+      run: |
+        micromamba create -p ./wasm-env \
+          --platform=emscripten-wasm32 \
+          --channel https://prefix.dev/emscripten-forge-4x \
+          --channel https://prefix.dev/conda-forge \
+          xeus-cpp=0.10
+    - name: Build Jupyterlite distribution
+      run: |
+        micromamba run -n jupyterlite-builder \
+          jupyter lite build \
+            --XeusAddon.prefix=./wasm-env \
+            --contents include/ \
+            --contents notebooks/ \
+            --output-dir ./dist
+    - name: Upload artifact
+      uses: actions/upload-pages-artifact@v3
+      with:
+        path: ./dist
+
+  deploy:
+    needs: build
+    if: github.ref == 'refs/heads/master'
+    permissions:
+      pages: write
+      id-token: write
+    environment:
+      name: github-pages
+      url: ${{ steps.deployment.outputs.page_url }}
+    runs-on: ubuntu-24.04
+    steps:
+    - name: Deploy to GitHub Pages
+      id: deployment
+      uses: actions/deploy-pages@v4
diff --git a/notebooks/simple.ipynb b/notebooks/simple.ipynb
new file mode 100644
index 000000000..e40969542
--- /dev/null
+++ b/notebooks/simple.ipynb
@@ -0,0 +1,207 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2efd7be2-5ea7-42cb-a2e2-9ddb409bc893",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#include <cstddef>\n",
+    "#include <vector>\n",
+    "#include <random>\n",
+    "#include <iostream>\n",
+    "\n",
+    "#include <xsimd/xsimd.hpp>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6f498bff-4366-4e1c-ab25-3d3589740e78",
+   "metadata": {},
+   "source": [
+    "Comparing two implementation of element wise mean."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cf6b2c85-1427-49a3-8bef-0340601319e8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "std::vector<double> random_vector(std::size_t n)\n",
+    "{\n",
+    "    static std::mt19937 gen(42);\n",
+    "    std::uniform_real_distribution<double> dist(0.0, 1.0);\n",
+    "    std::vector<double> v(n);\n",
+    "    for (auto& x : v)\n",
+    "    {\n",
+    "        x = dist(gen);\n",
+    "    }\n",
+    "    return v;\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a2ab6177-60e2-4d65-b323-51a6a21ad530",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "std::vector<double> mean_scalar(const std::vector<double>& a, const std::vector<double>& b)\n",
+    "{\n",
+    "    std::size_t size = a.size();\n",
+    "    std::vector<double> res(size);\n",
+    "    for (std::size_t i = 0; i < size; ++i)\n",
+    "    {\n",
+    "        res[i] = (a[i] + b[i]) / 2;\n",
+    "    }\n",
+    "    return res;\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "082ed2cd-273a-4c3c-a206-03b1efe49482",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "std::vector<double> mean_simd(const std::vector<double>& a, const std::vector<double>& b)\n",
+    "{\n",
+    "    using b_type = xsimd::batch<double>;\n",
+    "    std::size_t inc = b_type::size;\n",
+    "    std::size_t size = a.size();\n",
+    "    std::vector<double> res(size);\n",
+    "\n",
+    "    // size for which the vectorization is possible\n",
+    "    std::size_t vec_size = size - size % inc;\n",
+    "    for (std::size_t i = 0; i < vec_size; i += inc)\n",
+    "    {\n",
+    "        b_type avec = b_type::load_unaligned(&a[i]);\n",
+    "        b_type bvec = b_type::load_unaligned(&b[i]);\n",
+    "        b_type rvec = (avec + bvec) / 2;\n",
+    "        rvec.store_unaligned(&res[i]);\n",
+    "    }\n",
+    "    // Remaining part that cannot be vectorize\n",
+    "    for (std::size_t i = vec_size; i < size; ++i)\n",
+    "    {\n",
+    "        res[i] = (a[i] + b[i]) / 2;\n",
+    "    }\n",
+    "    return res;\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5959864d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "// Print v[begin:end] as grayscale ASCII blocks (dark = 0, light = 1).\n",
+    "void print_grayscale(const std::vector<double>& v, std::size_t begin, std::size_t end)\n",
+    "{\n",
+    "    for (std::size_t i = begin; i < end; ++i)\n",
+    "    {\n",
+    "        // map value in [0, 1] to a 24-bit truecolor gray (256 levels)\n",
+    "        int gray = static_cast<int>(v[i] * 255);\n",
+    "        std::cout << \"\\033[38;2;\" << gray << \";\" << gray << \";\" << gray << \"m█\";\n",
+    "    }\n",
+    "    std::cout << \"\\033[0m\\n\";\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2068e201",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "std::size_t n = 1000;\n",
+    "std::vector<double> const a = random_vector(n);\n",
+    "std::vector<double> const b = random_vector(n);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9d5a7adc-5b55-4224-a4ca-5e438d1fc4d4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "auto const res_simd = mean_simd(a, b);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d279cd74-c397-4ea8-af15-3745f043f656",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "auto const res_scalar = mean_scalar(a, b);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a04ae145",
+   "metadata": {},
+   "source": [
+    "Each block is a value in `[0, 1]` shown as a grayscale shade (dark = low, light = high). The vector is drawn in chunks of 100, each chunk stacking input `a`, the SIMD mean, the scalar mean, and input `b`. The two mean rows should look identical, each sitting between its inputs."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "59ca84ad-8b97-4523-af0d-d3eca01b41d0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "std::size_t const width = 100;\n",
+    "for (std::size_t begin = 0; begin < n; begin += width)\n",
+    "{\n",
+    "    std::size_t end = std::min(begin + width, n);\n",
+    "    std::cout << \"a:      \";\n",
+    "    print_grayscale(a, begin, end);\n",
+    "    std::cout << \"simd:   \";\n",
+    "    print_grayscale(res_simd, begin, end);\n",
+    "    std::cout << \"scalar: \";\n",
+    "    print_grayscale(res_scalar, begin, end);\n",
+    "    std::cout << \"b:      \";\n",
+    "    print_grayscale(b, begin, end);\n",
+    "    std::cout << \"\\n\";\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "90b86fb4-0426-43fd-b5fc-8626ef8732a5",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "C++17",
+   "language": "cpp",
+   "name": "xcpp17"
+  },
+  "language_info": {
+   "codemirror_mode": "text/x-c++src",
+   "file_extension": ".cpp",
+   "mimetype": "text/x-c++src",
+   "name": "C++",
+   "nbconvert_exporter": "",
+   "pygments_lexer": "",
+   "version": "cxx17"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}