Portefini

Our team created a complex eCommerce platform that generates sets of male clothing items based on the chosen occasion, style, or clothing item. Men who want to look stylish but don’t want to spend hours on shopping are free to use a sophisticated ML algorithm that gives results immediately. The platform functions as an aggregator of more than 1000 brand e-shops, and users can purchase items of different brands through Portefini. In addition to generating full sets, the system shows items made by other brands similar by type and color that can also be purchased via the Portefini platform.

Aggregators allow people who want to create a business that won’t require production or manufacturing of goods. As a smart men’s wear brand aggregator, this platform is monetized by getting a percentage from each sale. The platform aggregates over thousand brands, targets only a male audience looking for getting a stylish outfit, offers shopping in one click, and shows various recommendations like “where to wear it” to simplify the purchasing process.

To meet our client’s requirements and goals, we used Python and Django for the backend, which is responsible for processes like Big Data mining and processing. The platform has multiple integrations with external services like ML-driven aggregator (Visenze), payment (Stripe), purchase tax calculation (TaxJar), and many others. We implemented delayed loading to optimize platform performance, and continuous integration to ensure users always get an up to date range of items. Additionally, we solved the problem with size unification with regular equations, so the platform’s backend makes sure that users don’t have a negative experience with brand size differences. The system is based on cloud solutions and micro-service architecture. After we created a separate microservice for marketing processes, features that were impossible to realize are now easy to implement.