runcell.dev — Analytics & Data

What is runcell.dev?

runcell.dev is an AI agent that works inside Jupyter, the popular interactive coding environment. It turns a plain-language question into an executed workflow: it plans notebook steps, writes Python, runs cells, and fixes errors as the work develops. Instead of just suggesting code, it carries the analysis forward, reading outputs and making decisions based on what actually happened.

What problem does it solve?

For data professionals, going from a business question to a reproducible, explainable result often means manually assembling every step, handling errors, and constantly switching between code, output, and interpretation. runcell.dev automates that loop: understand, plan, execute, inspect, and continue. It is built for work that has to survive beyond a single prompt or a single cell, turning messy exploration into clear, defensible notebook steps.

Who is it for?

It is designed for analysts, data scientists, and researchers who work in Jupyter and need more than a code suggestion tool. Use cases include data analysis (from question to reproducible code), data science (testing methods, building models, comparing results), risk and quantitative finance (analyzing markets and portfolios with diagnostics), and research experimentation (generating code, figures, and reproducible evidence). It is not for teams that avoid coding entirely or need a fully no-code analysis platform.

Key capabilities

The agent understands the notebook context—data, existing code, and the question—before planning the next step. It executes multi-step workflows in Jupyter, recovers from errors, and interprets tables, charts, and statistics. It also offers in-context assist: inspect a cell, ask about a transformation or error, and get a fix that respects surrounding cells and outputs. A 'learn by doing' mode lets you explore analytical approaches side by side with real outputs, so you can choose the best direction based on evidence.

• Autonomous agent — Turn a question into a full executed workflow: plan, write, run, and fix errors automatically.
• Multi-step workflows — Handle complex analyses without hand-assembling every notebook step.
• In-context assist — Inspect any cell, ask about a transformation or error, and get a fix that understands the surrounding code and outputs.
• Output reading — Interpret tables, charts, and statistics so the next decision is based on actual results.
• Learn by doing — Explore methods with runnable experiments and compare real outputs side by side.
• Error recovery — The agent fixes errors as the work develops, keeping your analysis moving.

runcell.dev pricing: from $0.

Free Plan

Start free — runcell.dev offers a free plan to get started with the AI agent in Jupyter. Install with $pip install runcell and begin asking questions.

Paid Plans

For advanced usage and higher limits, runcell.dev offers paid plans for teams and professionals. Consult the pricing page on the official website for current tiers and pricing details.

Free trial available with the free plan.

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