Practical essays from the seekon.me team on catalog data, product discovery, marketplace infrastructure, and AI-assisted shopping systems.
AI shopping assistants are changing how products get discovered, compared, and chosen. This article introduces a simple scorecard for understanding whether your product gives AI enough reason to trust it, explain it, and guide shoppers toward purchase.
Traditional ecommerce websites were built for human shoppers, not AI systems. As more consumers use AI to discover and compare products, vague descriptions and scattered product details create a new challenge: AI needs clearer, more structured information to make reliable recommendations. This is the AI commerce gap.
A short look at how product search helps shoppers find where to buy something they already know, while agentic discovery helps people solve a problem first and discover the right products through natural AI-guided conversation.
We describe a failure mode that emerges when a hierarchical taxonomy is stored as a flat list, the design alternatives we considered, and the solution we shipped.
