Banani

Overview

Banani is an AI-powered UI design tool that functions as a full-fledged copilot for interface creation. It generates ready-to-edit, multi-screen UI designs and interactive prototypes from a wide range of inputs: natural language prompts, design references, product requirement documents (PRDs), uploaded images, screenshots, or existing Figma links. Instead of starting from a blank canvas, product teams can simply describe what they need or provide a visual starting point, and the AI transforms that input into a structured, on-brand multi-screen interface within minutes. The result is designed to be actionable, not just a static mockup — every screen is part of a clickable prototype that mirrors real user flows.

At its core, Banani emphasizes speed, flexibility, and interaction. It generates multiple screens in a single pass, allowing designers and non-designers alike to quickly explore entire user journeys. The interactive prototype is a key differentiator: users can click on any element on the canvas, and the AI generates what the user would see after that action, creating a natural way to define and validate flows. Beyond click-based generation, Banani incorporates a conversational AI interface — you can chat with the copilot to adjust content, swap layouts, refine color palettes, or modify specific components. The system also provides AI-driven style customization, making it easier to maintain brand consistency across generated screens. For engineering teams, Banani includes an MCP (Model Context Protocol) server integration, which allows coding agents to consume design outputs directly and accelerate front-end implementation.

Banani is designed with a practical workflow in mind. After AI generates the UI, you can share a Banani project link with stakeholders for instant feedback, or export your designs to Figma for further refinement, to HTML/CSS for web development, or as images for quick documentation. This multi-channel export pipeline ensures that AI-generated designs do not remain isolated in a tool but can be integrated into existing design systems and development pipelines. On the privacy and security side, Banani states that everything you generate is private and not used for model training. Your data, inputs, and generated outputs are not tied to you as a user, and the platform leverages OpenAI’s latest models as a foundational AI layer while maintaining this privacy boundary.

Positioned as a productivity accelerator for product teams, Banani helps non-designers, product managers, startup founders, engineers, and lean teams produce high-quality visual designs without needing extensive design expertise. Professional designers can also use Banani as an AI copilot to offload the busywork and focus on higher-level problem solving. Whether you are wireframing a new feature, turning a product requirement into a visual prototype, exploring design variations from a screenshot, or preparing handoff-ready files for development, Banani reduces the UI design cycle from days to minutes. This speed not only accelerates internal decision-making but also improves cross-functional alignment, enabling teams to test ideas and gather feedback earlier and more often. By lowering the barrier to creation, Banani empowers anyone on the team to ship beautiful, on-brand interfaces.

Core capabilities

Text-to-UI Generation

Turn natural language prompts or product requirement docs (PRDs) into complete multi-screen UI designs instantly.

Reference-Based Creation

Generate new designs by uploading images, screenshots, or providing existing Figma links as visual references.

Interactive Clickable Prototypes

Click any element in the generated design to produce the next screen, enabling immersive user-flow exploration.

Conversational AI Editing

Refine layouts, content, and styles through a chat interface with the AI copilot.

AI Style Customization

Tailor generated designs to match your brand identity, visual language, and design system.

Export to Figma, HTML/CSS, or Images

Move designs seamlessly into industry-standard tools and code for further development.

MCP Server Integration

Expose design generation capabilities to coding agents via the Model Context Protocol for AI-assisted implementation.

Privacy-First Generation

Keep all generated content private, with no training on your data and no association between outputs and your identity.

Use cases

Generating wireframes and high-fidelity UIs from product requirement documents (PRDs)

Creating design variants from screenshots or existing Figma links

Prototyping multi-screen user flows with clickable interactions for demos and buy-in

Iterating on interface designs through real-time AI chat feedback

Exporting polished UI to Figma or HTML/CSS for seamless developer handoff

Accelerating front-end implementation by integrating with coding agents via MCP

Producing brand-consistent UI for MVPs and new features in hours, not days