Case study
A visual launch generator for brands — one mockup in, a full brand presence out.
Outcome: Built end-to-end in 3 days · live app · $100K Higgsfield App Contest entry
Threadline App
Small clothing brands and print-on-demand sellers rarely have studio resources — just a product mockup and a deadline. Threadline accepts a single mockup upload and generates a complete launch package: styled product photography, a lookbook video, UGC-style footage, and social captions, in minutes instead of weeks.
Higgsfield defines not only the visual style of the interface, but also the interaction logic itself: a brief-first workflow, a step-by-step flow, model selection based on the task, and built-in creative workflows. So the goal was not to invent a brand-new interface, but to shape Threadline so it felt native to the Higgsfield ecosystem while still having its own distinct product character.
A PNG/JPG of the print or flat-lay — the only thing the user has to provide.
Category, mood, scene, audience, copy tone — these drive the entire pack.
Photos, lookbook video, UGC clip, copy pack — ready to post.
Upload your mockup — add one product mockup and basic product details.
4 styled e-commerce shots per generation, one shoot's worth of poses, picking from Nano Banana 2 / GPT Image 2 / Soul 2.0 as the rendering engine.
UGC Video — handheld, candid, phone-camera-style clip — deliberately scripted to open on the opposite kind of shot from the Lookbook (tight and already-rolling vs. wide and already-moving), so the two videos read as two different moments of the same shoot instead of one template wearing two moods.
Cinematic, slow-motion runway-style clip, engine choice between Seedance 2.0 / Kling 3.0 / Veo 3.1 Lite.
Product description, ready-to-post captions, hashtags, and content ideas, generated through a real LLM call (the only place in the whole app where an LLM writes freely — every visual prompt is deterministic string composition, not LLM-authored).
An inline editor on any generated photo: type what to change ("remove the necklace, make the background lighter"), pick a model, and it regenerates that specific shot using itself as the reference — without rebuilding the whole pack.
Every photo and video ever generated is saved and browsable, chronologically merged (not "all photos, then all videos"), with type badges so photo vs. video is obvious at a glance.
Reopen any past generation, see its real stored prompt, pick a (possibly different) engine, and regenerate — chained from the original input image, not the prior output (more on why that distinction mattered below).
Every photo and video prompt is built from a typed vocabulary — category × mood × scene × audience × talent mode — via pure string-composition functions. Never an LLM improvising the brief.
— The Prompt Engine — Deterministic Composition
Same Model mode changes the actual sequence of API calls: the Photo Pack submits and completes first from the original mockup, and that finished photo then becomes the image reference for the Lookbook and UGC video jobs — real model consistency, not a text hint asking the model to "keep the same person." Mixed Cast skips this entirely: all three packs generate in parallel straight from the mockup.
The app never surfaces a raw API error. Every pack carries a silent fallback chain: if the chosen engine isn't available on the user's plan, Threadline automatically retries the next one in the fallback order, with zero raw API errors ever reaching the user. Any other failure (out of credits, gateway down, unknown error) breaks the chain immediately and shows plain, understandable text instead — no status codes, no provider jargon.
The product description, captions, hashtags, and content ideas are the one part of the app generated by a real LLM call rather than deterministic composition — required to return one strict JSON object, no markdown fences, no commentary, and explicitly instructed to avoid AI-cliché language and write like a real founder talking to real customers.
The platform's shared components carry desktop-first defaults worth checking before trusting them on mobile — and even when the responsive option already exists, it's easy to reach for the fixed one first.
Try Threadline for yourself