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Runcell - Jupyter AI Agent
✓ verifiedFreemium
Jupyter-native AI agent that remembers a data project across sessions and reads chart/plot outputs, not just code.
👁 170K/mo♥ 5.5K
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Cody
✓ verifiedPaid
Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.
👁 245K/mo
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Replit
✓ verifiedFreemium
AI app-building platform where autonomous coding agents build, test, and deploy full-stack web and mobile apps from a prompt.
Pricing
No public pricing
No public pricing
Enterprise: starting at $16K (includes AI feature credits, scales with team size)
Starter: $0/month (free daily Agent credits)
Core: $20/month billed annually, $25/month billed monthly (monthly credits included)
Pro: $95/month billed annually, $100/month billed monthly (monthly credits included)
Core features
- ✦Fast tensor operations
- ✦Differentiable tensors for gradient-based optimization
- ✦Network connectivity
- ✦Integration with Bun and Flashlight
- ✦Support for GPU computation with CUDA (Linux) and CPU computation (macOS)
- ✦Cross-session project memory recalling prior decisions and state
- ✦Autonomous execution of long, multi-step notebook tasks
- ✦Reads cell outputs (plots, tables, metrics), not just code
- ✦In-notebook cell-level assistance and error fixing
- ✦Installs directly into existing JupyterLab via pip, no new editor
- ✦Concept explanations with runnable example cells
- ✦Codebase-aware developer chat
- ✦AI code completions and inline edits
- ✦Customizable and shareable prompts
- ✦Automatic bug identification and debugging help
- ✦Context filters to exclude sensitive repos
- ✦Integrates with major code hosts and IDEs
- ✦Autonomous AI coding agent that builds and deploys apps end to end
- ✦Visual, code-connected design canvas for UI tweaks
- ✦Built-in database and one-click publishing/hosting
- ✦Parallel multi-agent task execution for large projects
- ✦Integrations with tools like Linear, Notion, and Excel
- ✦Convert web apps into mobile apps
- ✦Credit-based usage billing on paid tiers
Use cases
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Data scientists running multi-week model iteration projects
- →Domain experts (e.g. risk/fintech) who know the problem but not deep Python
- →Researchers wanting an agent that remembers project context across days
- →Analysts needing help understanding unfamiliar algorithms or libraries
- →Engineers asking questions about an unfamiliar large codebase
- →Teams standardizing common coding tasks with shared prompts
- →Developers debugging errors faster with AI-assisted context
- →Enterprises running large-scale code migrations
- →Non-developers building working apps by describing them in prompts
- →Teams prototyping business or mobile apps quickly
- →Developers offloading repetitive coding/coordination to an AI agent
- →Enterprises needing SSO and dedicated environments for AI app building
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