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Jupyter-native AI agent that remembers a data project across sessions and reads chart/plot outputs, not just code.
Enterprise AI agent control plane that orchestrates coding agents across the SDLC on any model, deployable on-prem or air-gapped.
Documentation platform for publishing accurate, AI-ready docs sites, with Git sync and an MCP server for AI tools.
AI app builder that turns chat prompts into working web apps and sites, with credit-based build and deploy.
AI app builder turning English prompts into full-stack apps with provisioned DB, auth and hosting; also hosts autonomous agents.
No public pricing
No public pricing
Free trial available
No public pricing
Free trial available
No public pricing
- ✦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
- ✦Orchestration of AI agents across the SDLC
- ✦Model-agnostic, bring-your-own-model support
- ✦On-prem, VPC, and air-gapped deployment
- ✦Hybrid Context Engine for codebase-scoped answers
- ✦Spec, Agent, and Chat modes
- ✦Reusable skills, tool permissions, and coding-standard rules
- ✦Publish structured documentation sites
- ✦Git sync for docs-as-code workflows
- ✦AI setup agent to build and import docs
- ✦GitBook MCP server for AI access
- ✦Enterprise controls
- ✦Free tier to start
- ✦Chat-to-app and website generation
- ✦Real-time prototype building
- ✦One-click deploy and hosting
- ✦Templates to start projects
- ✦Credit-based building with shared workspaces
- ✦You own your code and data
- ✦Natural-language full-stack app generation
- ✦Auto-provisioned Postgres, auth, storage and hosting
- ✦Full code ownership with GitHub export
- ✦Managed hosting for autonomous AI agents
- ✦200+ bundled AI models
- ✦MCP and CLI tooling
- →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
- →Migrating and modernizing legacy .NET code
- →Running autonomous feature and refactor workflows
- →Enforcing company coding standards across teams
- →Answering questions and debugging across large codebases
- →Publish product and API documentation
- →Maintain docs-as-code with Git sync
- →Make docs consumable by AI assistants
- →Import existing docs into a hosted site
- →Build web apps without coding
- →Prototype product ideas quickly
- →Create landing pages and sites
- →Ship internal tools
- →Ship a SaaS without an engineering team
- →Build internal tools from a description
- →Deploy always-on AI agents quickly
- →Provide infra for AI-coded apps