Fusion

Product Introduction

1. Fusion is an AI-powered visual development platform that integrates directly with GitHub repositories to generate and edit production-ready UI code while maintaining alignment with existing design systems and coding standards. It automates code generation through AI analysis of connected design assets and API contexts, then facilitates collaboration by opening Git branches, creating pull requests, and deploying live previews for every change. The platform supports both developers and non-developers in building and modifying UIs without compromising code quality or system consistency.

2. The core value of Fusion lies in bridging the gap between design intent and technical implementation by leveraging organizational design systems and codebases as foundational context for AI-driven development. It enables cross-functional teams to iterate faster, reduce manual coding efforts, and maintain parity between visual edits and production code. By automating Git workflows and enforcing coding standards, it ensures enterprise-grade scalability while democratizing UI development across technical and non-technical roles.

Main Features

1. Fusion connects directly to GitHub repositories to analyze and utilize existing components, design tokens, and API integrations, generating code that adheres to predefined patterns and quality benchmarks. Developers can configure rules for code structure, component usage, and styling constraints, which the AI enforces during visual editing or automated generation.

2. The platform imports Figma designs and converts them into functional code by mapping design elements to existing code components and design system tokens. It maintains layer hierarchy and styling fidelity while automatically applying responsive layout logic and accessibility best practices derived from organizational standards.

3. Teams can visually edit any UI element within Fusion’s interface, with changes propagating directly to the underlying codebase through automated branch creation and PR workflows. The platform provides granular control over styling adjustments, component property modifications, and data binding to backend services, all tracked as code diffs for full auditability.

Problems Solved

1. Fusion eliminates the disconnect between design updates and engineering implementation by automating the translation of visual changes into version-controlled code. This solves the bottleneck of manual UI coding and reduces the risk of design-system drift across teams.

2. The product targets enterprise development teams working with complex design systems, product managers coordinating cross-functional workflows, and designers seeking to validate technical feasibility during the prototyping phase. It also serves non-technical stakeholders requiring safe UI modification capabilities without direct code access.

3. Typical use cases include updating legacy UIs to match new design guidelines, rapidly prototyping feature variations with real backend connectivity, and enabling marketing teams to create on-brand landing pages without developer dependencies. It also streamlines A/B testing by allowing instant deployment of UI variants through controlled CI/CD pipelines.

Unique Advantages

1. Unlike generic AI code assistants, Fusion operates within the constraints of an organization’s specific design system and architecture, ensuring generated code meets pre-approved patterns. It integrates with existing Git workflows rather than creating parallel development environments, maintaining engineering team sovereignty over code reviews and deployments.

2. The platform’s AI trains exclusively on the connected codebase and design assets, avoiding reliance on public datasets that might introduce licensing conflicts or quality issues. Enterprise users can optionally integrate private LLMs via API keys while maintaining full data isolation under SOC 2 Type II compliance standards.

3. Competitive advantages include zero data retention policies for customer code, bidirectional synchronization between visual edits and code commits, and granular permission controls for enterprise governance. The platform’s ability to generate interactive previews with actual API data during the design phase significantly reduces QA cycles compared to static prototyping tools.

Frequently Asked Questions (FAQ)

1. How does Fusion ensure generated code matches our internal components? Fusion analyzes component APIs, prop types, and usage patterns from your repository to create an organization-specific AI model, ensuring generated code utilizes approved components with correct property configurations and styling hooks.

2. Can non-developers safely make UI changes without breaking existing functionality? Fusion enforces design system rules and component contracts during visual editing, preventing invalid configurations while providing live previews with real data. All changes undergo automated testing and code review workflows before merging.

3. What happens to unused branches or experimental UI variants? Fusion automatically cleans up stale preview environments and provides archiving tools for managing experimental branches. Teams can configure retention policies to align with existing Git repository management practices.

4. How does the Figma integration handle design-system synchronization? The plugin maps Figma components to code equivalents using shared identifiers, validates design tokens against development values, and flags inconsistencies during import. Designers receive immediate feedback on technical constraints during the prototyping phase.

5. Is Fusion compatible with monorepos or microfrontend architectures? The platform supports complex repository structures through path-based scoping rules, allowing teams to limit AI context to specific subdirectories or packages. Integration with Lerna, Nx, or Turborepo workflows is configurable via YAML templates.