01
Lock direction across every run.
Uwear treats art direction as a reusable production brief. Casting, lighting, framing, variation controls, product requirements, and automatic QA criteria travel together from one run to the next.
FASHN gives developers strong reusable inputs: saved model identities, inspiration and background references, prompts, and fixed seeds for reproducibility. What its public docs do not show is one governed direction object that carries casting, framing, styling rules, and acceptance criteria together across a collection. Choose Uwear when direction must govern the run, not parameterize a request.[6][5]
02
Coordinate the full catalog, not just an endpoint.
Uwear keeps catalog intake, direction, job status, automatic QA, retries, approvals, and delivery connected. The operating unit is the production run, even when the catalog spans many products and output types.
FASHN markets bringing a full catalog to life, and its API is genuinely automatable: async jobs, polling, webhooks, SDKs. But the public unit of work is one product image per request with one to four outputs, under default limits of 50 requests per minute and six concurrent predictions. The catalog logic (sequencing, QA, retries, delivery) is yours to build. Choose Uwear when you want the production system, not just the endpoint.[5][4][2]
03
Turn approved stills into on-model motion.
Uwear sends an approved on-model still into the video step, then produces motion for product pages and campaigns without starting a separate asset chain.
FASHN also chains stills into video: its Experimental image-to-video endpoint produces 5- or 10-second clips at up to 1080p, and its Agent can run create-then-animate sequences. Choose Uwear when video must inherit an approved still inside the same QA-governed production job.[8][7]
04
Keep automatic QA inside the production loop.
Uwear makes automatic QA an agent-driven, toggleable part of the job. Outputs that fail the selected checks remain in retry or review, so approved delivery stays separate from failed work. This is workflow control, not a blanket pass-rate or fidelity guarantee.
FASHN documents user-led review: generate, look, refine, repeat, with an Agent that follows instructions and an API that reports success or failure. No automatic garment-fidelity scoring, acceptance thresholds, or visual retry policy is published. At catalog volume, that review labor is the hidden line item. Compare who checks the work: your team per output, or the production loop itself.[7][4]
05
Model cost before the run starts.
Uwear publishes the self-serve credit price and the credit rate for each image and video model. Teams can estimate a run before buying credits, and agents can plan one over MCP with a costed brief approved before generation. Enterprise pricing remains sales-led because volume, invoicing, shared workspaces, implementation, and support extend beyond credit consumption.
FASHN deserves full credit here: per-output cost tables, a $0.075 on-demand credit, a $7.50 minimum, and free failed predictions make its unit economics unusually computable. The difference is what the credits operate and who drives them. Uwear credits fund the governed workflow around each generation, with direction, QA, and retries attached, and agents operate it through a remote MCP server with a costed brief approved before generation. FASHN offers a coding skill for developers to build against REST.[3][9]
