AI Product Assistant for an Online Store

The challenge

An online store with a deep, specialized catalog was losing shoppers who couldn't tell which product was right for them. The differences between items were nuanced, buyers asked the same pre-sale questions over and over, and the team couldn't answer fast enough to keep every visitor from bouncing.

The numbers below are representative of this type of engagement. Real figures are shared with prospective clients under NDA.

What we built

We embedded an AI shopping assistant in the storefront that can consult customers on any product in the catalog. It:

• Explains what each product is and how products differ
• Recommends the right item for a stated goal or use case
• Compares options side by side in plain language
• Cites the exact product pages its answers come from
• Stays inside catalog data — so it never invents specs or makes off-label claims

The assistant is available on the homepage and on every product page, pre-loaded with the context of the item the shopper is viewing.

The approach

1. Catalog ingestion — products, categories, and descriptions indexed for retrieval
2. Retrieval + grounding so answers stay tied to real products
3. Guardrails that keep claims accurate and compliant
4. Buy-flow handoff — the assistant links straight to add-to-cart
5. Analytics on questions asked, products recommended, and gaps

Results

Shoppers could self-serve product guidance instead of waiting on the team, pre-sale questions dropped sharply, and the assistant nudged buyers toward the right product with sourced, on-brand answers across the entire catalog.

Stack

A retrieval-augmented assistant over the live catalog, deployed on cloud infrastructure and embedded directly in the headless storefront.