All Malls in Your Pocket - Now with AI

Building a marketplace that unites multiple malls and real brands into one seamless platform is complex. The main challenge lies in integrating APIs from different stores, each brand has its own infrastructure, standards, and limitations, making data unification difficult but not impossible. Another major hurdle is delivery management, where multiple malls and sellers require a consistent, efficient logistics flow. Finally, the key differentiator for this startup is its AI capability: developing an algorithm that ensures buyers can find any product with 100% accuracy within one minute. Achieving this level of precision requires solving challenges around catalog standardization, data enrichment, multilingual search, and AI-driven recommendation logic.

We began by conducting a deep analysis of the global marketplace ecosystem, studying best practices from platforms like Amazon, Alibaba, and niche mall-focused apps. Our team also carried out competitive research to identify gaps in product discovery, seller onboarding, and logistics.
To align with market needs, we started integration pilots with over 10+ brands, testing API connections and delivery workflows. At the same time, we built end-to-end documentation and UX/UI designs, mapping every process from admin approval flows to AI search scenarios.We have already created an MVP model, launched it in beta version, and are actively testing, improving, and scaling it for broader use while continuing full development of the web and mobile apps.

• Results so far:
  
  
  • Successfully completed six months of design and documentation, ensuring clarity and scalability.
  
  
  • Released an MVP in beta, currently used for real testing and validation.
  
  
  • Established working API connections with pilot brands, proving integration feasibility.
  
  
  • Built the foundation of an AI-powered product search engine, already showing faster discovery rates in testing.
  
  
  • Developed a secure, modular architecture with multilingual support.
  
  
• Challenges:
  
  
  • API fragmentation: each store uses different data formats and levels of digital maturity, requiring custom adapters.
  
  
  • Delivery logistics: coordinating multiple malls and couriers into a single unified system is complex and requires new operational standards.
  
  
  • AI accuracy: training algorithms to achieve one-minute guaranteed product discovery across millions of SKUs remains a difficult but central challenge.
  
  
  • Scaling: moving from MVP to a fully scalable product requires optimizing infrastructure and preparing for high-volume traffic.

The project represents a transformational shift for retail in the region and beyond. For the first time, shoppers will have “all malls in their pocket”, a unified platform with real brands, trusted sellers, and AI-powered discovery. Sellers benefit from streamlined onboarding, wider visibility, and standardized processes, while buyers enjoy faster search, accurate product recommendations, and simplified delivery.
From a business perspective, this initiative proves that even in a fragmented market, API-driven integration and AI innovation can redefine online retail standards. The MVP and beta version have already validated demand, and scaling efforts are underway to prepare for mass adoption.

• Backend: Node.js with Express framework


• Language: TypeScript for type safety and maintainability


• Architecture: Modular, API-first design supporting integrations with multiple brands and malls


• AI Features: Intelligent search, personalized recommendations, multilingual NLP for product discovery


• Infrastructure: Cloud-based deployment with 99.9% uptime SLA and scalable microservices architecture


• Frontend: React.js for the Admin Panel and Next.js for the Buyer Panel


• Mobile: React Native