Retail & E-commerce
Traditional recommendation engines use collaborative filtering — 'people who bought X also bought Y.' But they don't understand WHY. Our knowledge graphs connect products, categories, attributes, seasons, and buying behavior for recommendations that truly understand customer intent.
The problems
Your recommendation engine doesn't understand product relationships.
Shallow recommendations
Collaborative filtering that doesn't understand semantic relationships between products.
Disconnected inventory
Stock, logistics, and pricing in separate systems.
Limited personalization
Generic experiences that don't reflect customer context.
Our solutions
Retail & E-commerce
Catalog graph
Products connected by attributes, compatibility, season, and usage context.
Contextual recommendations
AI that recommends based on real customer intent, not just history.
Unified inventory
Unified view of stock, pricing, and logistics in real time.