ÁRSzűrő – Large-Scale Product Feed Processing & Price Comparison Platform
CGAT designed the technical foundation for ÁRSzűrő, a large-scale product feed processing and price comparison platform built around supplier XML feeds, product normalization, partner offers, and scalable background processing.
Kiinduló helyzet
CGAT designed the technical foundation for ÁRSzűrő, a large-scale product feed processing and price comparison platform built around supplier XML feeds, product normalization, partner offers, and scalable background processing.
Üzleti probléma
ÁRSzűrő is a price comparison platform designed to collect and process large volumes of product data from multiple suppliers and online stores. The system is built around partner feeds, product normalization, offer management, and scalable processing logic. CGAT designed the architecture for feed ingestion, queue-based processing, locking, product mapping, and long-term scalability. The system separates supplier-specific offer data from normalized product information, allowing multiple partners to be connected to a shared product catalog structure. The platform is intended to handle XML and CSV feeds, partner-specific product identifiers, product images, prices, stock information, and future AI-assisted product enrichment. The architecture supports background workers, distributed processing, and database structures suitable for high-volume e-commerce data. This case study demonstrates CGAT’s experience with data-heavy e-commerce systems, supplier integration, marketplace logic, and scalable product data processing.
Feltárt ok
Ehhez a részhez még ügyfél által jóváhagyott, részletes adat szükséges.
Megoldási megközelítés
ÁRSzűrő is a price comparison platform designed to collect and process large volumes of product data from multiple suppliers and online stores. The system is built around partner feeds, product normalization, offer management, and scalable processing logic. CGAT designed the architecture for feed ingestion, queue-based processing, locking, product mapping, and long-term scalability. The system separates supplier-specific offer data from normalized product information, allowing multiple partners to be connected to a shared product catalog structure. The platform is intended to handle XML and CSV feeds, partner-specific product identifiers, product images, prices, stock information, and future AI-assisted product enrichment. The architecture supports background workers, distributed processing, and database structures suitable for high-volume e-commerce data. This case study demonstrates CGAT’s experience with data-heavy e-commerce systems, supplier integration, marketplace logic, and scalable product data processing.
Megvalósítás
Ehhez a részhez még ügyfél által jóváhagyott, részletes adat szükséges.
Következő lehetőség
Mutassa meg egy konkrét folyamatát, és segítünk kijelölni az első alacsony kockázatú javítási lépést.
Eredmény
Ehhez a részhez még ügyfél által jóváhagyott, részletes adat szükséges.
Projektadatok
A technológiai stack másodlagos bizonyítékként szerepel, nem az üzleti eredmény helyett.
Van hasonló folyamat a cégében?
Mutassa meg egy konkrét folyamatát, és segítünk kijelölni az első alacsony kockázatú javítási lépést.
Ingyenes folyamatfelmérés