Car wrap visualizer: from swatch guesswork to AI previews on your car.
AI-powered car wrap visualization platform for a Ukrainian auto-detailing boutique. Users upload a photo of their car, select a wrap film from the distributor's catalog, and see a photorealistic preview of the wrap applied — preserving the original background, environment, and lighting.
Challenge.
The car wrapping boutique — also a wrap film distributor — needed a way for customers to visualize wrap options on their own car before committing. Traditional methods (physical swatches, generic mockups) couldn't convey how a specific film would look on a specific vehicle in realistic conditions.
Solution.
Phase 1 — discovery and concept validation. Built a Telegram bot proof of concept where users could upload a car photo, select a film by colour and texture, and receive an AI-generated visualization. Tested multiple AI image models.
Phase 2 — the branded platform. After validating the concept with the team, designed and developed a full branded web platform with the film catalog, upload flow, and AI rendering pipeline. The backend serves as a mediator layer between the frontend and the AI models.
Impact.
The platform is live in production with active users. The client achieved a branded, exclusive visualization tool that differentiates them from competitors. It directly impacts conversion — customers can try before they buy — reduces decision friction, and likely reduces return and dissatisfaction rates. No specific metrics were shared.
Features.
AI utilization.
The core product is AI-native. It uses generative AI models (Flux Context Max, GPT HQ, Google Nano Banana 2) for photorealistic car wrap visualization. The AI preserves the original photo's background, environment and lighting while applying the selected wrap film texture and colour to the vehicle. A NestJS backend acts as an orchestration layer between the frontend and multiple AI model APIs.
