See runcell.dev in Action
Experience the power of AI-enhanced Jupyter notebooks through interactive demos. Watch how our agent transforms your data science workflow.
Interactive Learning Mode
AI teacher that explains concepts with live examples - perfect for learning differences between algorithms like K-means vs DBSCAN.
Autonomous Agent Mode
AI takes full control of your notebook, executing cells and completing complex workflows automatically.
Smart Edit Mode
AI assistant that helps you edit and improve your notebook with intelligent suggestions and code modifications.
AI-Enhanced Jupyter
Ask questions about your code, get AI-generated solutions, and receive smart recommendations for next steps.
Ready to transform your Jupyter workflow?
Put Data Science AI to Work in Your Notebook
Modern research teams crave tools that keep pace with the scale of their ideas. runcell introduces a data science AI companion that lives directly in JupyterLab, watching every cell and waiting to assist. When you highlight a question or describe a transformation in plain language, the agent proposes code that matches your style and references the variables already in memory. This tight feedback loop helps scientists stay in the flow and keeps experiments moving instead of stalling on boilerplate.
The data science AI model inside runcell constantly scans the surrounding notebook context. It reads markdown notes, interprets charts, and follows the evolution of your datasets. Rather than offering generic snippets, the agent tailors suggestions to the structure of your project and the libraries you rely on most. You can ask the model to plot a distribution, clean a column, or engineer features for a machine learning experiment, and it will write the code and run the cells so you can immediately inspect the results.
Building a rich analysis often requires combining many small tasks, and the runcell agent excels at stringing those tasks together. The data science AI can refactor earlier cells, add missing imports, and suggest reusable functions that make notebooks cleaner. It also explains the reasoning behind each edit, creating a narrative that teammates can follow. Beginners get interactive guidance, while veterans enjoy faster execution for routine chores.
Security and privacy are baked into the design. The core data science AI runs in the browser, and heavy computations are delegated to secure APIs that never retain your data. This architecture lets enterprises benefit from cutting-edge models without compromising control. Whether you are exploring sensitive health records or proprietary financial metrics, runcell keeps the workflow compliant and confined to your environment.
Collaboration becomes easier when everyone can see how the analysis unfolded. runcell’s data science AI annotates key cells, summarizes outputs, and encourages consistent documentation. Share a notebook with colleagues and they’ll immediately understand the steps the agent took, making peer review and onboarding smoother. Teams can reproduce results, compare branches, and maintain a living record of decisions.
The more you work with runcell, the more capable the data science AI becomes. It learns from each interaction, adapting to project conventions and personal preferences. Over time the agent anticipates the next query or chart you’re likely to need, turning JupyterLab into a proactive environment rather than a passive editor. Analysts free up time for interpretation and storytelling, while researchers push models further with less manual setup.
Ready to experience this data science AI firsthand? Install the runcell extension and invite the agent into your notebooks. Within minutes you'll have an intelligent partner that transforms experiments into polished, reproducible workflows and keeps your focus on discovery.