Runcell Features
Discover how runcell transforms your Jupyter workflow with AI-powered features. Watch detailed demos and see each capability in action.
Quick intro to runcell - See how it transforms your Jupyter workflow
Give it a goal, it runs the notebook
Describe the outcome you want. Runcell plans the steps, writes the code, executes the cells, and fixes errors as it goes — an autonomous agent working end to end inside your notebook.
Multi-step workflows, executed for you
Key Benefits:
- Fully autonomous notebook execution
- Complex workflow automation
- Reduces manual repetitive tasks
- Smart error handling and recovery
Ask about any cell, apply the fix in one click
Select a cell and ask what is wrong or what comes next. Runcell reads the surrounding code and outputs, generates the fix, and recommends your next step — all without leaving the notebook.
AI that understands the cells around it
Key Benefits:
- Natural language queries about your code
- AI-powered code generation
- Smart recommendations for next steps
- Seamless Jupyter integration
Understand unfamiliar code with live examples
Hit an algorithm or library you do not know well? Runcell explains it with runnable examples right in your notebook — like comparing K-means vs DBSCAN on real data instead of digging through docs.
Concepts explained with runnable cells
Key Benefits:
- Interactive explanations with live code examples
- Step-by-step algorithm comparisons
- Visual learning with real-time execution
- Perfect for data science education
You bring the domain, the agent writes the code
For domain experts who think in problems, not Python. Describe the analysis or figure you need — like a genomics circos plot — and Runcell handles the implementation.
Research-grade code, minus the boilerplate
Key Benefits:
Ready to Transform Your Jupyter Workflow?
Join thousands of data scientists and researchers who are already using runcell.dev to supercharge their notebook experience.