import Layout from "@theme/Layout";
import BrowserOnly from "@docusaurus/BrowserOnly";
import Footer from "../components/footer/Footer";
import SplitSection from "../components/layout/SplitSection";
import Section from "../components/layout/Section";
import SectionSeparator from "../components/layout/SectionSeparator";
import CardGrid from "../components/layout/CardGrid";
import Card from "../components/layout/Card";
import Banner from "../components/layout/Banner";
import Rocket from "/img/notebooklink/rocket.svg";
import LinkToNotebookLink from "../components/LinkToNotebookLink";
import styles from "./notebooklink.module.css";
function NotebookLinkContent() {
return (
<>
Browser-native scientific computing. Large-scale deployments, no server, no setup, no limits.
Notebook.link delivers a full Jupyter environment running entirely in the browser — powered by WebAssembly. No installation, no server spin-up, no IT ticket. Click the link, start computing.
Built on JupyterLite and emscripten-forge, our open-source stack that brings the complete scientific ecosystem — NumPy, SciPy, Pandas, Matplotlib, and hundreds more including in C, R, Fortran and other languages — to any modern browser. The compute runs on your users' devices, not our servers. That means it scales to any number of users for the cost of file storage.
The technology has been tested to deploy notebooks to tens of thousands of concurrent users — just from standard static web servers. Zero compute infrastructure cost per user.
JupyterLite — the same engine powering notebook.link — has been tested with hundreds of thousands of users.
Compared to JupyterHub, or other commercial platforms. Because users bring their own compute, we only add the comfort layer, your cost remains low.
More users don't mean more servers. Browser-based execution means your platform scales without your costs scaling with it.
Replace JupyterHub for your institution. No containers per student, no DevOps burden, no IT tickets. LMS integration via LTI. Gradable notebooks with encrypted solutions.
Share reproducible work as a link. Byte-identical WASM environments mean your results are reproducible — not just in theory, but in practice. Computational irreproducibility costs billions annually.
Give internal analysts a Jupyter environment without the security overhead of local installs or the cost of per-user cloud kernels. SSO, RBAC, and audit logging on the roadmap. Backend kernels still available on demand.
Let millions of visitors interact with your data — including geospatial datasets via JupyterGIS or other advanced IDEs — without provisioning a single compute server. Data stays in the browser, GDPR-compliant by architecture.
Let AI agents access compute environments and run real calculations right in the browser, like Claude Code but sandboxed, safe and available on the fly.