Kombai

Product Introduction

1. Kombai is a domain-specific AI agent designed exclusively for frontend development tasks, capable of generating entire application UIs, refactoring code, and creating components from inputs like Figma designs, text prompts, images, or existing code.
2. Its core value lies in its specialized context-engine and tooling, which enable it to deliver unmatched fidelity in code output, adherence to coding best practices, and accelerated development velocity for frontend teams.

Main Features

1. Kombai interprets Figma designs with high accuracy using built-in deep-learning models, generating production-ready code that matches complex layouts, responsive behaviors, and interactive elements directly from design files.
2. The AI leverages Retrieval-Augmented Generation (RAG) systems trained on 30+ frontend libraries (e.g., React, Tailwind CSS, MUI) to enforce coding standards, ensure consistency with existing codebases, and optimize component reusability across projects.
3. Kombai integrates directly into IDEs like Cursor, providing codebase-aware assistance through purpose-built indexing tools that analyze repository structure, component libraries, and tech stacks to suggest contextually relevant implementations during development.

Problems Solved

1. Kombai addresses the inefficiency of generic AI coding tools in handling real-world frontend tasks, such as translating intricate Figma designs into functional code or maintaining consistency across large-scale component libraries.
2. It targets frontend developers and engineering teams working with modern frameworks like React, TypeScript, and SaaS platforms, particularly those managing complex UIs or design systems.
3. Typical use cases include converting Figma prototypes into responsive React components, adding features like user role management to existing applications, and building website builders or CMS-driven interfaces with stack-specific optimizations.

Unique Advantages

1. Unlike generic AI models (e.g., Gemini, Sonnet), Kombai combines domain-specific training with contextual awareness of frontend architectures, achieving 72% code review pass rates versus 50% for competitors and 96% compilation success rates versus 70% for alternative solutions.
2. Its innovative Figma parser resolves design-to-code challenges like spacing interpretation, dynamic value handling, and asset optimization, while its preview system lets developers audit AI-generated plans before code changes.
3. Competitive advantages include SOC2-certified data privacy, enterprise-grade customization through org-specific context engines, and native support for 25+ frontend libraries with framework-specific RAG optimizations.

Frequently Asked Questions (FAQ)

1. What frontend libraries does Kombai support? Kombai natively supports React, TypeScript, Tailwind CSS, MUI, Ant Design, and 20+ other libraries, with RAG systems trained on documentation and best practices for each framework.
2. How does Kombai integrate with development workflows? It operates directly within IDEs like Cursor, indexes local codebases to understand project-specific components, and provides inline code generation/refactoring without requiring external platforms.
3. Is my code data used for training? No—Kombai is SOC2-certified and never uses customer code or designs for model training, with all data processing confined to isolated, encrypted environments.
4. Can it handle complex Figma designs with animations? Yes, its deep-learning models parse layer relationships, interactive states, and design tokens to generate code with dynamic logic (e.g., form validation, multi-step modals) and CSS-in-JS implementations.
5. Does Kombai work for enterprise-scale projects? Enterprise plans include custom context engines for proprietary stacks, priority support for large codebases, and compliance with internal security protocols through on-premises deployment options.