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AI app builder that turns chat prompts into working web apps and sites, with credit-based build and deploy.
Kiro is a spec-driven agentic coding tool for IDE, CLI and web that turns prompts into specs and catches bugs with property-based tests.
Jupyter-native AI agent that remembers a data project across sessions and reads chart/plot outputs, not just code.
AI app builder that lets non-developers describe an idea and generate a working mobile or web app through chat.
Browser-based platform for building and hosting web apps collaboratively; the service appears to be winding down.
No public pricing
No public pricing
No public pricing
No public pricing
- ✦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
- ✦Spec-driven development (requirements, design, tasks)
- ✦Parallel agents, local or cloud
- ✦Property-based and correctness testing
- ✦Works in IDE, CLI, web and mobile
- ✦Multiple models (Claude, open-weight, Auto)
- ✦Headless CLI for CI/CD
- ✦Context from tools like Figma and Terraform
- ✦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
- ✦Natural language to app generation
- ✦Support for both mobile and web app output
- ✦Deployment-ready output with responsive UI
- ✦Credit-based usage pricing pegged to AI provider costs
- ✦Rollover, non-expiring credits
- ✦Mobile companion app for building on the go
- ✦In-browser code editor
- ✦Instant hosting for web apps
- ✦Remix and fork existing projects
- ✦Real-time collaboration
- ✦Community-shared apps
- →Build web apps without coding
- →Prototype product ideas quickly
- →Create landing pages and sites
- →Ship internal tools
- →Turning prompts into maintainable, spec-matched code
- →Catching bugs unit tests miss
- →Reviewing PRs and fixing bugs in CI/CD
- →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
- →Founders prototyping a mobile app idea without hiring developers
- →Non-technical users building internal tools or SaaS MVPs
- →Teams needing quick websites or content management systems
- →Developers experimenting with AI-assisted app scaffolding
- →Prototype web apps quickly
- →Host small Node.js and web projects
- →Remix and learn from community code
- →Collaborate on code in the browser