Best Agentic AI Platforms for Jupyter Notebook

Compare the Top Agentic AI Platforms that integrate with Jupyter Notebook as of April 2026

This a list of Agentic AI platforms that integrate with Jupyter Notebook. Use the filters on the left to add additional filters for products that have integrations with Jupyter Notebook. View the products that work with Jupyter Notebook in the table below.

What are Agentic AI Platforms for Jupyter Notebook?

Agentic AI platforms enable organizations to build, deploy, and manage autonomous or semi-autonomous AI agents that can plan, reason, and take actions across systems. These platforms provide tools for agent orchestration, memory management, tool integration, and decision-making workflows. They often support multi-agent collaboration, monitoring, and governance to ensure reliability and compliance. Many agentic AI platforms integrate with enterprise applications, data sources, and APIs to execute complex tasks end to end. By operationalizing intelligent agents, agentic AI platforms help businesses automate knowledge work and scale AI-driven operations. Compare and read user reviews of the best Agentic AI platforms for Jupyter Notebook currently available using the table below. This list is updated regularly.

  • 1
    Windsurf Editor
    The Windsurf Editor is a free AI-powered IDE and AI coding assistant that accelerates development by providing intelligent code generation and agents in over 70 programming languages and more than 40 IDEs, including VSCode, JetBrains, and Jupyter Notebooks. With Windsurf, developers can write code faster, eliminate repetitive tasks, and stay in the flow state—whether they're working with Python, JavaScript, C++, or any other language. Built on billions of lines of open-source code, Windsurf Editor understands and anticipates your coding needs, offering multiline suggestions, automated unit tests, and even natural language explanations for complex functions. It’s perfect for streamlining code writing, reducing boilerplate, and cutting down the time spent on documentation searches. Trusted by individual developers and Fortune 500 companies alike, Windsurf Editor is your go-to solution for boosting productivity and writing better code. Try Windsurf for free today!
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    Starting Price: Free
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  • 2
    BLACKBOX AI

    BLACKBOX AI

    BLACKBOX AI

    BLACKBOX AI is an advanced AI-powered platform designed to accelerate coding, app development, and deep research tasks. It features an AI Coding Agent that supports real-time voice interaction, GPU acceleration, and remote parallel task execution. Users can convert Figma designs into functional code and transform images into web applications with minimal coding effort. The platform enables screen sharing within IDEs like VSCode and offers mobile access to coding agents. BLACKBOX AI also supports integration with GitHub repositories for streamlined remote workflows. Its capabilities extend to website design, app building with PDF context, and image generation and editing.
    Starting Price: Free
  • 3
    Google Colab
    Google Colab is a free, hosted Jupyter Notebook service that provides cloud-based environments for machine learning, data science, and educational purposes. It offers no-setup, easy access to computational resources such as GPUs and TPUs, making it ideal for users working with data-intensive projects. Colab allows users to run Python code in an interactive, notebook-style environment, share and collaborate on projects, and access extensive pre-built resources for efficient experimentation and learning. Colab also now offers a Data Science Agent automating analysis, from understanding the data to delivering insights in a working Colab notebook (Sequences shortened. Results for illustrative purposes. Data Science Agent may make mistakes.)
  • 4
    Akira AI

    Akira AI

    Akira AI

    Akira.ai provides businesses with Agentic AI, a set of specialized AI agents designed to optimize and automate complex workflows across various industries. These AI agents collaborate with human teams, enhancing productivity, making real-time decisions, and automating repetitive tasks, such as data analysis, incident management, and HR processes. The platform integrates smoothly with existing systems, including CRMs and ERPs, ensuring a disruption-free transition to AI-enhanced operations. Akira’s AI agents help businesses streamline their operations, increase decision-making speed, and boost overall efficiency, driving innovation across sectors like manufacturing, finance, and IT.
    Starting Price: $15 per month
  • 5
    Scout

    Scout

    Scout

    Scout is a comprehensive platform that enables users to build, launch, and scale AI solutions efficiently. It offers a workflow builder for creating AI automations using models, web scraping, data storage, API calls, and customized logic. Users can set up automated content ingestion from various sources, including websites and documentation, and connect multiple large language models within a single workflow to find optimal solutions. Deployment options include Copilots for delivering AI-generated answers directly on websites, Slack integration for customer interactions, and APIs and SDKs for building custom AI applications at scale. Scout provides comprehensive testing and tuning features, including evaluations, real-time monitoring, and built-in logging to oversee workflow status, latency, and costs. The platform is trusted by teams building the future.
    Starting Price: $49 per month
  • 6
    runcell.dev

    runcell.dev

    runcell.dev

    Runcell is a Jupyter-native AI agent that understands your notebooks, writes code and executes cells so you can focus on insights, offering four AI-powered modes in one high-performance extension: Interactive Learning Mode provides an AI teacher that explains concepts with live code examples, step-by-step algorithm comparisons and real-time visual execution; Autonomous Agent Mode takes full control of your notebook to execute cells, automate complex workflows, reduce manual tasks and handle errors intelligently; Smart Edit Mode acts as a context-aware assistant, delivering intelligent code suggestions, automated optimizations and real-time syntax and logic improvements; and AI-Enhanced Jupyter lets you ask natural-language questions about your code, generate AI-powered solutions and receive smart recommendations for next steps, all seamlessly integrated into the familiar Jupyter interface.
    Starting Price: $20 per month
  • 7
    Edison Analysis

    Edison Analysis

    Edison Scientific

    Edison Analysis is a next-generation scientific data-analysis agent built by Edison Scientific. It is the analytical engine underpinning their AI Scientist platform, Kosmos, and it’s available both on Edison’s platform and via API. Edison Analysis performs complex scientific data analysis by iteratively building and updating Jupyter notebooks in a dedicated environment; given a dataset plus a prompt, the agent explores, analyzes, and interprets the data to provide comprehensive insights, reports, and visualizations, very much like a human scientist. It supports execution of Python, R, and Bash code, and includes a full suite of common scientific-analysis packages in a Docker environment. Because all work is done within a notebook, the reasoning is fully transparent and auditable; users can inspect exactly how data was manipulated, which parameters were chosen, how conclusions were drawn, and can download the notebook and associated assets at any time.
    Starting Price: $50 per month
  • 8
    NEO

    NEO

    NEO

    NEO is an autonomous machine learning engineer: a multi-agent system that automates the entire ML workflow so that teams can delegate data engineering, model development, evaluation, deployment, and monitoring to an intelligent pipeline without losing visibility or control. It layers advanced multi-step reasoning, memory orchestration, and adaptive inference to tackle complex problems end-to-end, validating and cleaning data, selecting and training models, handling edge-case failures, comparing candidate behaviors, and managing deployments, with human-in-the-loop breakpoints and configurable enablement controls. NEO continuously learns from outcomes, maintains context across experiments, and provides real-time status on readiness, performance, and issues, effectively creating a self-driving ML engineering stack that surfaces insights, resolves standard settlement-style friction (e.g., conflicting configurations or stale artifacts), and frees engineers from repetitive grunt work.
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