Figma vs Unabyss: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Figma and Unabyss — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Figma
Figma, Inc.
Collaborative, web-based vector design and prototyping platform for building and iterating product interfaces with real-time feedback.
Key features
- Web-based Vector Editor: A browser-first vector graphics editor tailored for UI and UX design, enabling designers to create scalable interface assets without installing native software.
- Prototyping and Mobile Preview: Built-in prototyping tools to link screens and interactions, plus Figma Mirror companion apps for Android and iOS to preview prototypes on real devices.
- Real-time Collaboration: Multiple users can simultaneously edit files, leave comments, and gather feedback in-context, streamlining design reviews and cross-discipline collaboration.
- Desktop Apps with Offline Access: Native macOS and Windows desktop applications provide additional offline functionality while syncing with the cloud workspace.
- Plugin and API Ecosystem: Extensible platform with official plugin samples, community plugins, and APIs available via Figma's GitHub organization for automating tasks and adding integrations.
- Design System & Team Libraries: Support for shared libraries, components, tokens, and versioned resources to maintain consistent design systems across teams and projects.
- Web-based vector graphics editor with desktop apps for macOS and Windows
- Real-time multi-user collaboration with live cursors, comments and version history
- Interactive prototyping and mobile preview via Figma Mirror (iOS/Android)
- Design Systems: shared libraries, components, styles, and tokens
- Plugin ecosystem and Plugin API (JavaScript/TypeScript) for custom tools and automations
- REST API and developer SDKs for programmatic access to files, components and assets; sample repos available on GitHub
- Export options: SVG, PNG, JPG, PDF and CSS code snippets for assets and components
- Developer handoff features: specs, measurements, and code snippets for front-end implementation
- FigJam for collaborative whiteboarding and design workshops
- Offline support via desktop apps and community-maintained Linux builds
Best for
- Collaborative Interface Design: Teams co-create and iterate on web and mobile app interfaces in real time, reducing handoff friction and centralizing feedback.
- Interactive Prototyping and User Testing: Build interactive prototypes and preview them on actual devices via Figma Mirror to validate flows and interactions with stakeholders or testers.
- Design System Governance: Create, publish, and maintain shared component libraries and design tokens to enforce visual consistency across products and teams.
- Plugin Development and Custom Workflows: Develop custom plugins or use community plugins (via Figma's plugin ecosystem) to automate repetitive design tasks and integrate external tools.
- Accessibility Annotation and Review: Use specialized plugins and libraries (e.g., accessibility annotation plugins) to document and review accessibility-relevant design details before handoff.
- Cross-platform Design Workflows: Work seamlessly across browser and desktop environments, enabling designers on different OSes to collaborate on the same files and projects.
- Design teams creating and iterating UI/UX for web and mobile applications with simultaneous collaboration
- Prototyping interactive flows and testing on mobile devices using Figma Mirror
- Maintaining cross-team design systems and shared component libraries
- Automating design workflows and extending functionality via custom plugins and integrations
- Developer handoff: exporting assets, inspecting components, and providing specs for implementation
Unabyss
Unabyss
Self-updating universal context layer that provides segmented, persistent context to agents and LLMs via the MCP connector protocol.
Key features
- Self-Updating Context Layer: Continuously ingests and refreshes relevant documents, events, and interaction history so connected agents always receive current context without manual updates.
- MCP-Native Connector: Exposes context through the MCP connector protocol, enabling any MCP-capable agent or LLM to request and consume the same shared context surface.
- Segmented Access Controls: Context is segmented by default to enforce boundaries between projects, users, or data classes, reducing accidental exposure of private information.
- Persistent Cross-Session Memory: Stores and surfaces long-lived context across sessions, addressing short-lived model memory and improving multi-step task continuity.
- Automatic Context Prioritization: Selects and supplies the most relevant context for a given prompt or agent task, reducing prompt size and minimizing irrelevant data sent to models.
- Agent-Agnostic Integration: Works with multiple agents and LLM backends (via MCP), allowing teams to centralize context management without coupling to a single model provider.
- Persistent, session-spanning context storage to address short-term memory limits
- Self-updating context that automatically evolves without manual prompt engineering