Find Similar Designs is an AI retrieval feature that helps teams discover visually related assets in large files or libraries. It supports consistency by linking discovery to your Design System and optional Style Reference inputs.

Text-to-Image Generation creates visuals directly from prompt instructions. Most modern systems rely on a Diffusion Model and can be steered using a Reference Image.

A Reference Image is a conditioning input that guides composition, structure, or aesthetics during generation. It is central to Style Reference workflows and Multi-image Conditioning.

Multi-image Conditioning uses several images as control inputs for one generation task, improving consistency across outputs. It extends single Reference Image workflows in Text-to-Image Generation.

Segment Anything Model (SAM) produces masks from points, boxes, or text-like prompts for rapid object selection. It underpins modern Image Segmentation workflows and improves control in Reference Image editing.

Subject-Driven Generation aims to keep a specific person, product, or character consistent across new generated scenes. It is often implemented with DreamBooth and guided by a Reference Image.

Reference recreation is the process of rebuilding a design from an image, URL, or example while preserving its layout, style, and visual hierarchy.

In AI-assisted website creation, reference recreation helps teams move faster without losing control of structure, content, performance, or editable design details.