AI SaaS202602 / 06
Fotovyn
An AI product photography and visual content platform for e-commerce sellers, fashion brands, creators, and agencies.
Role
Founder & sole engineer — AI pipelines, product, platform
Stack
- Next.js
- TypeScript
- Diffusion model APIs
- Queue workers
- PostgreSQL
- Object storage
The problem
Product photography is the single largest recurring cost for small e-commerce sellers — studio time, models, reshoots for every variant. Generic image models get you a nice picture, not a usable catalogue asset with the right product, the right framing and the right consistency across a range.
Approach
- 01Built seven distinct visual workflows — studio shots, lifestyle scenes, model try-ons and more — rather than one generic prompt box, so each job runs a pipeline tuned to its output.
- 02Grounded generation in the seller's actual product images so the result is their item, not a plausible lookalike.
- 03Ran everything through a durable job queue with explicit states, so a slow or failed generation is visible and retryable instead of silently lost.
- 04Made cost observable per generation — the platform is only viable if the unit economics stay legible to both the seller and the operator.
Outcome
- Seven production visual workflows in one platform.
- Catalogue-ready output without booking studio time.
Next project
Menuvyn