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Spread Fashion - AI-Powered Print Design and Personalisation App
Mobile App
commercial
Created byMemory Squared
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Overview
An AI-powered mobile app that enables users to generate, edit and personalise fashion products through an intuitive mobile experience connected to Spread Group’s large-scale commerce and production ecosystem.
Project Details
Category
Mobile App
Customer
SpreadGroup
Submitted by
Memory Squared
Timeframe
June 2025 - ongoing
Tech Stack
React Native, Expo, TypeScript, LangChain, Swift, Kotlin
Services
Product Discovery, AI Research, Product Strategy, UX/UI Design, Cross-platform Mobile Application Development, Systems Integration
Team
PM: Adam Policht
Development: Konrad Łomzik, Bartłomiej Gigoń, Staszek Greń, Szymon Konopek, Rafał Rybarczyk
Design: Adam Policht, Kristina Sedelnikova, Mateusz Cygan
+ Spread Group product and engineering teams
Link to case study
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Description
Spread Group is an international fashion and lifestyle company specialising in on-demand production and printing across a portfolio of apparel and merchandise brands.
The cooperation began with a focused research assignment. Spread Group wanted to understand whether generative AI could meaningfully improve the creation of visual designs and print-ready assets, particularly within a native mobile environment.
At the time, the company already operated a mature and commercially successful web ecosystem, including a browser-based product editor and AI-assisted design capabilities. The main product challenge was therefore not simply to transfer existing functionality onto a smaller screen. It was to determine what role mobile should play within a complex, established commerce and production environment.
Research and validation
The initial phase combined product discovery with technical research into generative AI models and image-processing infrastructure.
We assessed potential solutions in terms of:
- Output quality and consistency
- Operational cost
- Scalability
- Generation time and performance
- Integration complexity
- Reliability under realistic usage conditions
- Potential impact on user experience and conversion
The research showed that visual quality alone was not a sufficient measure of suitability. A model producing impressive individual results could still be unsuitable for a commercial product because of cost, latency, limited controllability or unreliable output.
We therefore designed and tested multiple generation and processing pipelines, including different prompt structures, preprocessing methods and post-processing flows. These experiments helped establish which capabilities were sufficiently stable and controllable to become part of a real product.
From research to MVP
The engagement gradually evolved from research into product development.
Together with Spread Group, we defined a focused mobile MVP centred around an AI-assisted editor. The objective was to allow users to generate and personalise designs without exposing the technical complexity.
Building within an enterprise ecosystem
The application could not operate as an independent product. It had to connect with Spread Group’s existing:
Product catalogue
Authentication and account systems
Commerce APIs
Rendering infrastructure
Production workflows
Product configuration logic
Logistics systems
Some of these systems were also evolving while the mobile application was being developed. This required close coordination between teams and an architecture capable of accommodating changes without destabilising the user experience.
The UX challenge was equally significant. We needed to create a modern, mobile-first product while maintaining continuity with a design language and commerce ecosystem developed over many years.
The build-versus-reuse decision
One of the most important decisions concerned the design editor.
Building a complete mobile editor from scratch - including AI capabilities, product configuration and integration with production systems - would have required substantial time and investment. It would also have created a rigid development cycle in a rapidly changing AI market.
Spread Group already used an editor within its web environment. Although the existing solution was not originally designed for this mobile use case and required significant adaptation, it provided a proven technical foundation.
Working with Spread Group, we chose to adapt this core instead of replacing it. The work focused on:
Redesigning interaction patterns for mobile
Simplifying complex editing flows
Creating a cohesive UX around the existing engine
Extending the native SDK where necessary
Connecting the editor to Spread Group’s wider infrastructure
This decision reduced time to market while preserving the stability of an established technology foundation. It also allowed the team to concentrate more effort on the product experience and the elements that genuinely differentiated the application.
Release and continued development
The first production version was released in February 2026.
Following the launch, the project moved into continuous development. The application has evolved beyond a mobile extension of the existing website and is becoming a standalone way to enter and use the Spread Group ecosystem.
Ongoing work includes:
Usability and onboarding improvements
Deeper commerce and ordering integration
Authentication and account flows
Product configuration
New AI-assisted capabilities
Sharing and collaboration
Template-based creation
Richer product presentation formats
The project demonstrates how generative AI can become part of a practical commercial product when it is combined with disciplined product strategy, thoughtful mobile UX and deep integration with real operational systems.
It also shows that meaningful innovation does not always require rebuilding every component. In this case, the strongest solution came from combining existing technology, custom mobile development and new AI workflows into one coherent product.
Project Outcomes
The project evolved from a short generative AI research engagement into a production mobile application released in February 2026 and now developed continuously as a standalone entry point into Spread Group’s ecosystem.
Key outcomes include:
- Successfully introduced AI-assisted product personalisation into Spread Group's mature commerce and production ecosystem.
- Delivered a production-ready React Native application integrated with authentication, commerce, rendering, production and logistics systems.
- Reduced time-to-market by extending an existing editing platform instead of rebuilding complex functionality from scratch.
- Established a foundation for continuous product evolution, including AI capabilities, collaboration features and improved creative workflows.
- Over 5,000 personalised products created through the mobile application.
- Achieved an end-to-end conversion rate exceeding 6%
- 34% of orders include an upsell, indicating strong user engagement and effective product presentation.
- 5.0 Rating in App Store
The product also established an effective collaboration model between a small, agile delivery team and a large international organisation with multiple stakeholders and mature technical infrastructure.
Target Audience
The application is designed for consumers who want to create and purchase personalised apparel and merchandise directly from their phones.
It particularly addresses younger and mobile-first users who are comfortable creating visual content. The product reduces the complexity of AI image generation, graphic editing and product configuration into an accessible, guided flow.
Users can generate visual concepts, edit them, apply them to physical products and move naturally towards ordering - without needing to understand the AI models, production processes or technical systems operating behind the experience.
Why Us
We believe AI innovation is not about replacing proven products, but about extending them with capabilities that deliver real customer value. For Spread Group, we integrated AI-powered personalisation into a mature commerce platform.
https://apps.apple.com/pl/app/spread-fashion-design-share/id6747127900


