Will it recommend products I don't have?

No. Recommendations are constrained to your synced catalog with stock-aware filtering. The agent is honest when it can't find a fit — it won't invent SKUs or hallucinate features.

How is this different from Shopify's built-in recommendations?

Shopify recommendations are rule-based (frequently bought together, related products) shown in static UI blocks. Upsell Buddy is conversational — the customer describes a problem, the agent recommends. Different surface, different intent.

What about upsell and bundle logic?

The agent runs offer logic alongside recommendations: 'one offer per response' is the default to avoid spam. Bundles surface only when relevant; upsell suggestions tie to the product the customer is actually viewing or asking about.

Recommendations vs upselling — what's the difference?

Recommendation = answer the customer's question with the right product. Upsell Buddy = grow basket size with a higher-tier or complementary item. Upsell Buddy handles both, but treats them as different jobs with different triggers.

Recommend from your real catalog

AI product recommendations from your real catalog.

Upsell Buddy vector-searches your live products and recommends what's in stock. Real SKUs, real variants, real fit. The agent is honest when it can't find a match — no hallucinated recommendations.

Start free

No credit card
5-step setup
Works on any site

Works on Shopify, WooCommerce, WordPress, and custom storefronts

Shopify WooCommerce WordPress Custom sites

AI product recommendations — A conversational recommendation engine that vector-searches your live ecommerce catalog, applies intent detection to figure out what the customer actually needs, filters by stock and variant availability, and surfaces real, in-stock products — not hallucinated SKUs.

Quick verdict

Most stores have hundreds of products. Most visitors browse a handful. Upsell Buddy closes the gap with conversational recommendations from your real catalog — vector search over synced products, intent-detection, stock-aware filtering, one-offer-per-response etiquette.

How it works

Three layers between question and recommendation

Vector search over your real catalog

Recommendations come from your synced products with stock + variant awareness. Not pulled from training data, not made up.

Intent detection first, products second

The agent figures out what the customer actually needs before retrieving — so 'I'm hiking the JMT in August' returns the right tents, not a random list.

One offer per response

Default behavior is one recommendation, one offer per turn. Stops the spam-card pattern that trains buyers to ignore your widget.

Live on the storefront

Conversational recommendations in action

Upsell Buddy widget recommending real products from a synced catalog, with stock-aware filtering — Widget recommends real products from your live catalog

vs static recommendations

Conversational beats rule-based

Shopify rule-based recommendations

"Frequently bought together," related-products grids, static blocks. Surface products without knowing what the customer is actually trying to do.

Upsell Buddy conversational recommendations

Customer describes their need; the agent retrieves matching products from your live catalog, filters by stock, and recommends one. The customer feels heard.

FAQ

Common questions

Upsell Buddy vector-indexes your live product catalog (Shopify, WooCommerce, or manual). When a visitor asks a question, the agent runs intent detection, retrieves the most relevant products from your catalog, filters by stock and variant availability, and recommends what's actually buyable.

Ready in minutes

Help customers find the right product. Today.

14-day free trial. AI included. Sync your catalog and start recommending in minutes.

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