FASHN

About FASHN

FASHN develops image-based generative models for the fashion industry, offering a virtual try-on solution that allows users to visualize garments with pixel-perfect accuracy. This technology addresses the challenge of online shopping by providing a realistic fitting experience, enhancing customer confidence and reducing return rates.

```xml <problem> Online fashion retail suffers from high return rates due to customers' inability to accurately visualize how garments will look on them. Traditional virtual try-on solutions often lack realism and fail to meet the quality expectations of fashion brands. </problem> <solution> FASHN provides an image-based generative AI model specifically designed for the fashion industry, enabling realistic virtual try-on experiences. Their solution allows users to visualize garments on themselves with pixel-perfect accuracy, addressing a key challenge in online apparel shopping. By offering a high-fidelity virtual fitting experience, FASHN aims to increase customer confidence, reduce return rates, and improve the overall online shopping experience for fashion consumers. The technology is available through a web application and an API for integration into existing e-commerce platforms. </solution> <features> - Pixel-perfect garment rendering, maintaining resemblance to the original item - Background preservation, ensuring the focus remains on the garment and user - Support for versatile poses, allowing users to visualize the garment in different positions - Input flexibility, accommodating various user-provided images - Available through a web application and API for commercial use </features> <target_audience> FASHN's primary customers are fashion brands and online retailers seeking to enhance their e-commerce platforms with realistic virtual try-on capabilities. </target_audience> ```

What does FASHN do?

FASHN develops image-based generative models for the fashion industry, offering a virtual try-on solution that allows users to visualize garments with pixel-perfect accuracy. This technology addresses the challenge of online shopping by providing a realistic fitting experience, enhancing customer confidence and reducing return rates.

Where is FASHN located?

FASHN is based in Tel Aviv, Israel.

When was FASHN founded?

FASHN was founded in 2023.

Who founded FASHN?

FASHN was founded by Aya Bochman.

  • Aya Bochman - Co-Founder
Location
Tel Aviv, Israel
Founded
2023
Employees
6 employees
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FASHN

Score: 75/100
AI-Generated Company Overview (experimental) – could contain errors

Executive Summary

FASHN develops image-based generative models for the fashion industry, offering a virtual try-on solution that allows users to visualize garments with pixel-perfect accuracy. This technology addresses the challenge of online shopping by providing a realistic fitting experience, enhancing customer confidence and reducing return rates.

fashn.ai500+
Founded 2023Tel Aviv, Israel

Funding

No funding information available. Click "Fetch funding" to run a targeted funding scan.

Team (5+)

Aya Bochman

Co-Founder

Company Description

Problem

Online fashion retail suffers from high return rates due to customers' inability to accurately visualize how garments will look on them. Traditional virtual try-on solutions often lack realism and fail to meet the quality expectations of fashion brands.

Solution

FASHN provides an image-based generative AI model specifically designed for the fashion industry, enabling realistic virtual try-on experiences. Their solution allows users to visualize garments on themselves with pixel-perfect accuracy, addressing a key challenge in online apparel shopping. By offering a high-fidelity virtual fitting experience, FASHN aims to increase customer confidence, reduce return rates, and improve the overall online shopping experience for fashion consumers. The technology is available through a web application and an API for integration into existing e-commerce platforms.

Features

Pixel-perfect garment rendering, maintaining resemblance to the original item

Background preservation, ensuring the focus remains on the garment and user

Support for versatile poses, allowing users to visualize the garment in different positions

Input flexibility, accommodating various user-provided images

Available through a web application and API for commercial use

Target Audience

FASHN's primary customers are fashion brands and online retailers seeking to enhance their e-commerce platforms with realistic virtual try-on capabilities.

FASHN | StartupSeeker