Generic AIs struggle with complex frontend tasks. With specialized context-engine and tooling, Kombai delivers unmatched fidelity, code quality, and, dev velocity.
Kombai significantly outperforms generic coding agents + Frontier models + MCPs in building UX from Figma, image, or text based prompts. Read more.
% Review criteria passed (avg by task)
Kombai
Gemini 2.5 Pro + Agent¹
Sonnet 4 + Agent¹ + MCPs²
Sonnet 4 + Agent¹
Gemini 2.5 Pro + Agent¹ + MCPs²
% Features verified in test (avg by task)
Kombai
Gemini 2.5 Pro + Agent¹
Sonnet 4 + Agent¹ + MCPs²
Sonnet 4 + Agent¹
Gemini 2.5 Pro + Agent¹ + MCPs²
% Outputs compiled successfully
Kombai
Sonnet 4 + Agent¹
Sonnet 4 + Agent¹ + MCPs²
Gemini 2.5 Pro + Agent¹
Gemini 2.5 Pro + Agent¹ + MCPs²
1. Agents used: Aider when without MCP, OpenAI agent + CodeMCP, OR Filesystems MCP when with MCP. All agents were allowed 3 attempts to fix errors.
2. MCPs used: Context7 for documentation, Framelink for Figma designs.
Kombai's built-in deep-learning models can code real-world Figma designs with unmatched fidelity.
With specific, human-tested RAGs, Kombai can use supported libraries with higher accuracy & consistency.
Kombai has indexing and search tools purpose-built for Frontend codebases. Using these, it can find and reuse relevant code faster, and with higher accuracy.
Kombai works for frontend projects of all sizes and complexities.
Kombai won't mistakenly change your database or backend logic.
For enterprise customers, we set up custom context-engines that can accurately use complex stacks.
Kombai is Soc2 certified. It never uses your data for training or model improvements.
From small components to full app UIs - Kombai generates frontend code right inside your IDE. Get clean, backend-agnostic output that fits your stack and repo.
