Banani

Banani is a figma design generator tool that turns plain text prompts into editable, multi-screen UI prototypes. Banani generates editable, multi-screen UI prototypes from text prompts, reference images, screenshots or Figma links. It offers an AI canvas for design iteration, one-click sharing, and export to Figma, HTML/CSS and images.

Banani is an AI UI design tool that converts written prompts, reference images, screenshots, Figma links, or product requirement documents into editable multi-screen interfaces. The product targets people who need working screens quickly: product managers sketching a flow for a spec, founders validating an app idea, engineers who lack a designer, and design teams that want the repetitive layout work handled before they refine details. Small design shops and students are also in the audience the site names. In practice the workflow starts in a browser based canvas. A user describes the product in ordinary language and Banani returns several connected screens rather than one static mockup. From there, iteration happens two ways: selecting an element and asking the AI to change it, or typing a chat instruction such as making the layout more playful or more minimal. Colors, typography and other design tokens can also be tuned by hand, which keeps the output from looking like a generic template. Reference images and screenshots can be dropped in so the tool matches an existing visual style or reproduces a screen closely. Delivery is handled through sharing and export. A project or single screen can be sent as a link for teammate feedback, and finished work moves out as Figma files, HTML/CSS, or flat images. The same designs can be exposed to coding agents through an MCP connection, which is the most interesting part for teams already building with AI coding tools. Banani positions itself against both traditional design software and prompt-to-app builders. It stops at the design layer rather than generating a running application, so the comparison is really with Figma plus a plugin, or with Lovable and Base44 style tools where UI generation is bundled into code output. The team describes the product as a copilot rather than an autonomous designer, so expect to steer it.