
Client Success Story
AI Fashion Social Mobile App: From Inherited Code to Production

Project Overview
From Legacy Code to a Production-Ready Social Ecosystem
A Berlin-based fashion social mobile app for enthusiasts to share outfits, discover styles, and interact through core social features with AI-powered tagging.
Fashion/Social Media
Germany, Berlin
Ongoing
$25K
Strategy & Execution
How We Stabilized the Codebase & Shipped AI-Powered Tagging
This was a startup-style engagement: move fast, ship a stable beta, and design the architecture to scale without burning money.
Our approach focused on: Completing and stabilizing an inherited codebase, improving maintainability and delivery speed.
Implementing AI-assisted tagging (LLM API) to improve content organization and discovery.
Shipping a production-ready mobile experience, aligned with social app expectations (feeds, profiles, interactions).
Building scalable infrastructure with cost trade-offs in mind (ready to grow, but lean for early-stage usage).
Setting up monitoring and maintenance workflows to keep the app stable post-launch.
Staying highly responsive to a startup environment with flexible hours and proactive problem solving.
When issues appeared (including developer fit), we handled it quickly by swapping developers fast and smoothly, keeping delivery on track.

Challenges in Scaling Content Discovery & Stability
The founder needed a reliable partner to: Add a meaningful AI feature (not 'AI for hype'), specifically automatic tagging to help users categorize and discover fashion content.
Take over partially completed work from another developer and finish the MVP.
Deliver a working beta quickly, without sacrificing core quality.
Build an infrastructure that would be scalable, but still optimized for early-stage budgets.
Ensure ongoing maintenance, monitoring, and feature rollouts as the product evolves.

Working Beta and Product Foundation
We delivered a working beta and product foundation that included:
KEY FEATURES IMPLEMENTED:
- 01
AI-Powered Tagging (LLM Integration)
We implemented AI-driven tagging via an LLM API to support automatic tagging of user-generated fashion images/content, improved content organization and searchability, and better discovery experiences for users browsing styles and categories. This feature helped the app feel smarter and more 'social-feed ready' without requiring a complex custom ML pipeline at MVP stage.
- 02
Full-Stack Product Delivery
We completed both frontend and backend development, turning early work into a cohesive product with stable performance and clean workflows.
- 03
Scalable Infrastructure with Cost Trade-Offs
We designed infrastructure to handle expected growth while keeping early-stage costs under control, with clear upgrade paths as traction increases.
- 04
Monitoring + Maintenance Setup
We set up monitoring and support processes to detect issues early and keep the app stable during testing and rollouts.
- 05
Ongoing Feature Rollouts + Startup Guidance
We supported the founder with best-practice advice, product decisions, and a flexible roadmap approach as priorities shifted.
Project Interface Showcase
Client Testimonials
What Our Clients Say
Feedback on how our innovative solutions help achieve business results.

Xedrum delivered a production-ready AI-powered application within the agreed timeline and budget, including a working release on Apple TestFlight. The team was highly proactive in resolving issues, adapting to evolving requirements, and ensuring the AI functionality aligned with real user needs. Throughout the engagement, Xedrum consistently treated the project as a priority and demonstrated a strong understanding of both technical and business concerns.
Celine LeibfriedCEO at Unscripted
Xedrum successfully implemented a robust system that allows users to upload data, execute automated jobs, and retrieve results efficiently. The team delivered all components on schedule, maintained clear communication through weekly and ad-hoc meetings, and demonstrated professionalism throughout. The final solution met both technical and operational expectations.
Tomer PeretzCTO at Osirix
Xedrum's engineers worked closely with the client's project manager, integrating seamlessly into the existing workflow. The team consistently delivered planned milestones, maintained strong communication through regular online meetings, and brought a personal, collaborative approach that made them feel like an in-house AI team rather than an external vendor.
FredericCTO at Touch2Seen
Xedrum operated as an extension of the client's internal team, taking ownership of both delivery and day-to-day execution. Their engineers quickly understood the product context, collaborated across time zones, and proactively contributed ideas to improve the solution. The team maintained consistent velocity, adapted to changing priorities, and helped move the product forward without adding management overhead.
Arnon ZamirCTO at Aristo
Xedrum successfully implemented a robust system that allows users to upload data, execute automated jobs, and retrieve results efficiently. The team delivered all components on schedule, maintained clear communication through weekly and ad-hoc meetings, and demonstrated professionalism throughout. The final solution met both technical and operational expectations.
Richard BatesCEO at Acumen Data
Xedrum delivered a production-ready AI-powered application within the agreed timeline and budget, including a working release on Apple TestFlight. The team was highly proactive in resolving issues, adapting to evolving requirements, and ensuring the AI functionality aligned with real user needs. Throughout the engagement, Xedrum consistently treated the project as a priority and demonstrated a strong understanding of both technical and business concerns.
Celine LeibfriedCEO at Unscripted
Xedrum successfully implemented a robust system that allows users to upload data, execute automated jobs, and retrieve results efficiently. The team delivered all components on schedule, maintained clear communication through weekly and ad-hoc meetings, and demonstrated professionalism throughout. The final solution met both technical and operational expectations.
Tomer PeretzCTO at Osirix
Xedrum's engineers worked closely with the client's project manager, integrating seamlessly into the existing workflow. The team consistently delivered planned milestones, maintained strong communication through regular online meetings, and brought a personal, collaborative approach that made them feel like an in-house AI team rather than an external vendor.
FredericCTO at Touch2Seen
Xedrum operated as an extension of the client's internal team, taking ownership of both delivery and day-to-day execution. Their engineers quickly understood the product context, collaborated across time zones, and proactively contributed ideas to improve the solution. The team maintained consistent velocity, adapted to changing priorities, and helped move the product forward without adding management overhead.
Arnon ZamirCTO at Aristo
Xedrum successfully implemented a robust system that allows users to upload data, execute automated jobs, and retrieve results efficiently. The team delivered all components on schedule, maintained clear communication through weekly and ad-hoc meetings, and demonstrated professionalism throughout. The final solution met both technical and operational expectations.
Richard BatesCEO at Acumen Data
Related Work
Similar Cases

AI/ML
Mobile App
HIPAA
RAG
AI-Powered Healthcare MVP for Patient Imaging Insights
A New York-based healthcare MVP that helps patients better understand their medical imaging results through AI-assisted explanations in plain, human-readable language.

AI/ML
Cloud Infrastructure
AWS
ETL
Data Pipeline
Cloud-Based AI & ETL Platform for Agricultural Machine Learning
A cloud-native system capable of orchestrating AI workloads, managing data pipelines, and storing results for an AgriTech company specializing in machine learning for field crop analysis.

RAG
AI/ML
FinTech
SQL
Azure OpenAI
RAG-Powered Natural Language to SQL for Accounts Payable Automation
A proof of concept using RAG architecture to enable non-technical users to interact with accounting data through natural language queries translated into secure SQL.

RAG
FinTech
Process Automation
AI/ML
UK Compliance
RAG-Powered Process Automation for a Fintech Platform
A RAG-powered automation layer that enables teams to retrieve accurate information, automate internal workflows, and reduce manual processing across finance and operations.

SaaS
MarTech
Node.js
React
PostgreSQL
AI-powered SaaS Dashboard
A high-performance analytics platform that automates marketing reporting by aggregating data from major ad networks into a unified AI-driven intelligence hub.

AI/ML
Mobile App
HIPAA
RAG
AI-Powered Healthcare MVP for Patient Imaging Insights
A New York-based healthcare MVP that helps patients better understand their medical imaging results through AI-assisted explanations in plain, human-readable language.

AI/ML
Cloud Infrastructure
AWS
ETL
Data Pipeline
Cloud-Based AI & ETL Platform for Agricultural Machine Learning
A cloud-native system capable of orchestrating AI workloads, managing data pipelines, and storing results for an AgriTech company specializing in machine learning for field crop analysis.

RAG
AI/ML
FinTech
SQL
Azure OpenAI
RAG-Powered Natural Language to SQL for Accounts Payable Automation
A proof of concept using RAG architecture to enable non-technical users to interact with accounting data through natural language queries translated into secure SQL.

RAG
FinTech
Process Automation
AI/ML
UK Compliance
RAG-Powered Process Automation for a Fintech Platform
A RAG-powered automation layer that enables teams to retrieve accurate information, automate internal workflows, and reduce manual processing across finance and operations.

SaaS
MarTech
Node.js
React
PostgreSQL
A high-performance analytics platform that automates marketing reporting by aggregating data from major ad networks into a unified AI-driven intelligence hub.

Don't wait — let's talk today.
Hi, I'm Danylo Melnychuk
CEO at Xedrum
Start Your Project
Looking for a reliable tech partner? We handle the technical implementation so you can focus on scaling your business.



