Banani

Banani's core capability converts natural language descriptions into structured UI layouts within seconds. The AI interprets intent for layout structure, component placement, color schemes, and typographic hierarchy from plain English prompts. For example, a prompt like 'a SaaS dashboard with a left sidebar, top metrics row, and a data table with pagination' produces a layered, editable layout with each component individually selectable. The output is not a flat image but a structured design with discrete layers, meaning users can click on any element to reposition, resize, or restyle it after generation. More specific prompts — including color preferences, layout direction, and component details — yield more targeted results, while vague prompts produce reasonable defaults based on common UI conventions.

Unlike one-shot generation tools, Banani supports iterative refinement through follow-up text instructions that apply targeted changes without regenerating the entire design. Users can say 'move the sidebar to the right' or 'change the header background to dark blue' or 'add a search bar above the table' and the tool modifies the existing layout in place. This conversational loop preserves prior work and allows incremental shaping of a design through dialogue, which is faster and more predictable than regenerating from scratch with a modified prompt. The refinement model is particularly useful for non-designers who may not know exactly what they want upfront but can react to what they see and guide the design iteratively.

The platform includes a library of 12 or more pre-trained UI component types spanning common elements such as buttons, cards, navigation bars, modals, tables, form elements, toggle switches, avatars, badges, tooltips, and progress indicators. These components are not generic placeholders — they are styled with modern design conventions including appropriate padding, border radius, shadow depth, and typographic sizing. When the AI generates a layout, it selects and arranges components from this library based on the prompt context, producing designs that feel coherent rather than assembled from mismatched parts. The library covers the most common UI building blocks, though highly specialized components (e.g., code editors, map widgets, or calendar pickers) may not be available as pre-trained types.

Banani supports export in 3 formats: PNG on the Free tier for quick sharing and stakeholder review, and SVG plus Figma-compatible formats on paid plans (starting at $12/month for Plus) for scalable vector assets and seamless handoff into production design workflows. The Free tier also includes 3 Figma exports per day. Code export via MCP is available on Plus ($12/month) and Pro ($30/month) plans.

Generated designs follow contemporary UI conventions by default, including readable body text sizing, consistent grid spacing for alignment, and clear visual hierarchy through size and weight contrast. While users should verify that generated layouts meet their specific brand guidelines and accessibility requirements, the defaults produce visually credible mockups without requiring manual adjustment of basic design properties like padding, margin, font size, and color contrast. This is particularly valuable for non-designers who may not know standard spacing or typography conventions, as the output looks professional enough to present to stakeholders or include in pitch materials without extensive post-generation styling work.