aicoolies logo

Onlook vs Lovable vs Tempo Labs — Visual React Builders & AI App Development Compared

Visual React development has become a distinct category in 2026, with tools that let designers and developers manipulate real React components through intuitive visual interfaces rather than writing code line by line. This comparison examines three platforms leading this shift: Onlook as an open-source visual editor that connects to your existing codebase, Lovable as a conversational full-stack app builder for rapid product creation, and Tempo Labs as a visual React IDE with multi-agent AI planning and a rich editing canvas.

Analyzed by Raşit Akyol on March 31, 2026

Share

What Sets Them Apart

The gap between design and development has been one of the most persistent friction points in software creation. Designers produce mockups in Figma, developers rebuild them in code, and the back-and-forth translation introduces delays, inconsistencies, and frustration. The three tools in this comparison represent a new generation of visual development environments where the visual representation and the code are the same artifact. Each takes a different approach to achieving this unity, from editing existing codebases visually to generating new applications from descriptions.

Buildship, n8n, and Zapier at a Glance

Onlook is an open-source visual editor with over 22,000 GitHub stars that connects directly to existing React, Next.js, and Vue projects. Unlike tools that generate code from scratch, Onlook works with your real components, styles, and project structure. Designers drag and drop real React components on an infinite canvas, make visual changes to layouts and styles, and submit pull requests for engineers to review. Changes sync to code in real time, meaning what you design IS the code. Onlook supports Tailwind CSS, CSS modules, styled-components, and works with any component library.

Lovable is a conversational AI application builder that generates complete full-stack web applications from natural language descriptions. Users describe what they want through a chat interface, and Lovable produces a working application with React frontend, Supabase backend, database schema, authentication, and deployment, all in a single session. The platform handles the entire lifecycle from generation through iterative refinement to production deployment, making it possible for non-technical founders to create functional web products without writing a line of code.

Tempo Labs, a Y Combinator S23 company, has evolved from a visual React editor into a full prompt-to-app platform with a unique multi-agent planning approach. When given a description, Tempo deploys multiple AI agents that collaborate on architecture, user flows, and screen breakdowns before writing any code. The resulting plan is visible as flow diagrams that users can review and adjust. Once generation begins, Tempo provides a visual editor for tweaking components with drag-and-drop, with changes modifying the actual React code underneath. It is specifically optimized for Vite and Tailwind CSS.

AI Capabilities, Backend, and Integrations

The fundamental architectural difference lies in whether these tools edit existing code or generate new code. Onlook is designed to work with your existing codebase, connecting to projects already in development and providing visual editing on top of real components. Lovable and Tempo both generate new projects from scratch, creating applications from descriptions rather than modifying existing ones. This distinction determines when each tool is most valuable: Onlook for ongoing development and refinement, Lovable and Tempo for initial creation and prototyping.

For designer-developer collaboration, Onlook offers the most direct workflow. Designers work on a visual canvas using familiar tools, while every change automatically generates clean React code that appears as a pull request for engineers to review. This preserves the code review process that engineering teams rely on for quality control. Tempo provides collaboration through shared visual editing where team members can iterate on the same interface. Lovable's conversational approach makes collaboration happen through the shared chat interface where anyone can contribute ideas.

Code quality and ownership differ across platforms. Onlook guarantees clean code because it modifies your existing code with direct manipulation rather than generating new code, producing no unnecessary wrappers or style bloat. Tempo generates clean React code optimized for Vite and Tailwind, with the visual editor maintaining code quality during subsequent edits. Lovable generates working applications with proper structure but the code quality may vary for complex features, and teams who need deep customization typically export and continue development in their own IDE.

Pricing and Learning Curve

AI capabilities serve different purposes in each tool. Onlook's AI assists with component generation from descriptions, design suggestions, and responsive layout optimization within the context of your existing project. Tempo's multi-agent system creates detailed architecture plans before generating code, and its AI retains context across iterations for efficient refinement. Lovable's AI handles the full-stack complexity including database design, API creation, authentication setup, and deployment configuration, going deeper into backend territory than the other two tools.

Pricing reflects different business models and target audiences. Onlook is open source and can be self-hosted for free via GitHub, with a hosted cloud version available for teams who want managed infrastructure. Lovable offers a free tier for exploring and paid plans that increase generation credits and feature access. Tempo provides a free tier with limited usage and a paid plan starting at $50 per month for full access. All three offer significantly more value per dollar than traditional development when measured by time-to-functional-interface.

The Bottom Line

For teams with existing React codebases who want to empower designers to make visual changes that become real pull requests without touching code, Onlook provides the most elegant bridge between design and development with its open-source visual editing approach. For entrepreneurs and product teams who need to go from idea to deployed full-stack application with minimal technical involvement, Lovable offers the most complete generation pipeline from concept to production. For React-focused development teams who want the best combination of AI planning, visual editing, and code quality in a dedicated React IDE, Tempo Labs delivers a uniquely thoughtful development experience with its multi-agent architecture.

Quick Comparison

FeatureOnlookLovableTempo Labs
PricingSelf-hosted open source is free; hosted Starter is free with MCP-call limits; Teams is customFree tier / Starter $20/mo / Pro $50/moPaid subscription plans
PlatformsReact, Next.js, Storybook, shadcn/ui, GitWeb (browser-based)React, existing codebases, design systems
Open SourceYesNoYes
TelemetryCleanCleanClean
DescriptionOnlook is an open-source visual editor for React and Next.js with 25.9K+ GitHub stars that lets designers edit real code-backed interfaces on an infinite canvas. It connects visual changes, AI chat, component and layer inspection, and versioned code workflows so teams can prototype and refine product UI without treating design files as the source of truth.Build production-ready applications from text and image prompts. Full-stack with Supabase backend, authentication, and one-click deployment. Formerly GPT Engineer, backed by top investors. Targets non-technical founders and product teams who want to go from idea to deployed app in minutes, with AI handling both frontend UI and backend infrastructure setup.Tempo Labs is a YC-backed AI design and prototyping tool that generates and edits React code directly within a developer's existing codebase, maintaining project styles and conventions. Unlike tools that produce standalone code, Tempo supports both greenfield and brownfield projects, understanding existing component libraries, theme systems, and coding patterns to generate code that fits naturally.