AI in Commerce

Semantic search and recommendations are the familiar half. We connect them to your real catalogue and merchandising rules, so results respect stock, margin and brand constraints instead of quietly ignoring them, and so merchandisers keep the ability to override what a model suggests.

The newer half is agentic shopping readiness. Assistants are beginning to browse and buy on a customer behalf, and they never see your storefront — they see your feeds, your structured data and your APIs. That means feeds carrying availability and price accurately, schema.org/Product markup deep enough to answer a specific question, and checkout endpoints an agent can traverse without a human clicking through.

We treat this as an audit before a build: what an agent can discover about your products today, where it would fail, and which of those gaps are worth closing now. The same structured product data also improves how your catalogue reads in ordinary search, so the work is not a bet on a single future.