Service for selecting goods after completing a survey
The project was developed as a standalone web service deployed on a dedicated server using the feedcraft.space domain. The backend is built with Node.js, hosted on a VPS, and managed with PM2 to ensure stability, automatic restarts, and scalability.
The backend is responsible for handling the survey logic, storing user responses, applying business rules, and selecting relevant products. Product data is obtained through integration with the Horoshop e-commerce platform API. Products are regularly fetched, normalized, and stored in a local database to enable fast processing, filtering, and reliable recommendation logic.
The frontend is implemented as a separate client application that communicates with the server via an API. Users complete a step-by-step survey, where each answer dynamically influences the subsequent flow and the final result.
The diet recommendation service analyzes pet parameters such as pet type, age, activity level, individual needs, and dietary purpose. Based on these inputs and structured product characteristics, the system generates a personalized product selection. Recommendations are built using structured attributes rather than simple tags, resulting in more accurate and relevant outcomes.
The final output of the service is a curated list of recommended products, which can be used as an independent tool or integrated into an e-commerce system for further customer interaction.
The backend is responsible for handling the survey logic, storing user responses, applying business rules, and selecting relevant products. Product data is obtained through integration with the Horoshop e-commerce platform API. Products are regularly fetched, normalized, and stored in a local database to enable fast processing, filtering, and reliable recommendation logic.
The frontend is implemented as a separate client application that communicates with the server via an API. Users complete a step-by-step survey, where each answer dynamically influences the subsequent flow and the final result.
The diet recommendation service analyzes pet parameters such as pet type, age, activity level, individual needs, and dietary purpose. Based on these inputs and structured product characteristics, the system generates a personalized product selection. Recommendations are built using structured attributes rather than simple tags, resulting in more accurate and relevant outcomes.
The final output of the service is a curated list of recommended products, which can be used as an independent tool or integrated into an e-commerce system for further customer interaction.
Kyiv 
Available for hire