FitSure

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  FitSure by Cartor Labs — evidence-based fashion purchase decision copilot

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  Purchase Brief and garment candidates

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  Decision Board with real YouCam Apparel Virtual Try-On result

Inspiration

Online fashion shoppers can see an item, but still struggle to decide whether it is worth buying for a specific need.

FitSure was built around that decision: compare a small set of garment candidates against the same Purchase Brief, understand the trade-offs, and make a more informed choice before checkout.

What it does

FitSure is an evidence-based fashion purchase decision copilot.

A shopper enters a Purchase Brief with their occasion, formality, budget, wardrobe context, expected use, and priority. They then upload a customer photo and garment image.

FitSure uses YouCam Apparel Virtual Try-On to generate one real try-on at a time. The resulting image is presented inside a Side-by-Side Decision Board alongside locally structured evidence for the selected garment candidates.

The board provides contextual Buy, Consider, or Skip for this purpose verdicts, comparative trade-offs, and a clear confidence boundary.

How we built it

FitSure is a Next.js web application with a server-side YouCam integration.

The workflow uploads the user and garment images, creates a task with the YouCam Apparel Virtual Try-On API, polls the task until it reaches a terminal state, parses the generated image, and renders it in the Decision Board.

The product includes validation, timeout handling, duplicate-submission protection, polling cleanup, local image previews, file replacement and removal, and recovery guidance.

Challenges we ran into

The main challenge was making virtual try-on useful without overstating what an image can prove.

FitSure can support visual comparison, occasion alignment, color relationships, wardrobe context, and relative versatility. It cannot guarantee physical fit, comfort, fabric feel, construction quality, movement, or exact real-world color.

We also had to protect a limited API budget. The app intentionally runs one real try-on at a time and avoids automatic retries.

Accomplishments that we're proud of

We completed a real end-to-end Apparel Virtual Try-On validation in Production. A generated image was received, displayed in the Decision Board, and the polling flow stopped after success.

We are also proud that FitSure treats uncertainty as a product feature rather than hiding it behind a compatibility score.

What we learned

A virtual try-on image is not the final value. The value comes from connecting that visual result to a concrete purchase decision and explaining the compromise behind it.

What's next

Next, we would validate the workflow with more retail scenarios and explore a retailer-facing recovery flow that suggests a better alternative when a garment is not right for the shopper's stated purpose.

Built With

• api
• apparel
• artificial
• intelligence
• next.js
• try-on
• typescript
• vercel
• virtual
• youcam