AI Recommendation Engine for Shopify

AI Product Recommendations
That Actually Understand
Your Customers.

Personalized product recommendations powered by customer context, catalog intelligence, and brand-specific business logic.

Most engines rely on generic "You May Also Like" widgets.
This AI understands customer intent in real time and recommends based on:

Purchase history
Skin type / dietary needs
Bundle compatibility
Subscription behavior
Inventory rules
Product relationships
Customer goals
Brand policies

The result: higher conversion rates, increased average order value, and a more personalized shopping experience.

Works with Shopify subscription and DTC brands

Shopping Assistant

AI Active

Scenario:Skincare BundleLisa A.
LA
I just bought the daily moisturizer. What sunscreen would go well with it?
Ask about products...

Built From Real Context

Recommendations built from real customer context

Not shallow associations. The AI combines eight layers of signal to generate recommendations that actually make sense.

Customer behavior

Browsing patterns, page dwell time, and search intent signals.

Order history

What they bought, when, how often, and what they re-ordered.

Catalog metadata

Compatibility rules, complementary product flags, ingredient lists.

Compatibility logic

Product pairings that work together — and ones that don't.

Inventory availability

Never recommends out-of-stock or discontinued items.

Support interactions

Past tickets, preferences, and expressed product feedback.

Subscription data

Active subscriptions inform what to cross-sell vs. avoid.

Brand rules

Your policies, exclusion lists, and margin priorities.

Beyond "Related Products"

A different kind of recommendation engine.

Traditional Recommendation Engines

  • Static product associations

  • Generic "You May Also Like" widgets

  • No customer understanding

  • No contextual awareness

  • Same recommendations for everyone

  • Zero brand-rule enforcement

Milexi AI Recommendation Engine

  • Conversational recommendations

  • Real-time intent detection

  • Personalized logic per customer

  • Product compatibility awareness

  • Brand-policy enforcement

  • Dynamic bundling and upsells

  • Customer-specific cross-sells

How It Works

Five steps from customer intent to cart conversion

01

Understand Customer Intent

The AI analyzes what the customer is actually trying to accomplish — not just what they searched.

02

Reference Customer Context

Uses purchase history, subscriptions, preferences, and behavioral signals to build a complete picture.

03

Apply Catalog Intelligence

Evaluates compatibility, bundles, exclusions, inventory conditions, and your business rules.

04

Recommend The Best Next Product

The AI presents the most relevant recommendation conversationally — not as a widget, but as an answer.

05

Increase Conversion Automatically

The customer adds products naturally without aggressive selling. Higher AOV, better experience.

What The AI Can Recommend

Every type of recommendation, driven by context.

Complementary products
Bundles
Subscription add-ons
Product upgrades
Refill timing
Accessories
Seasonal recommendations
Personalized routines
Compatibility-based products
Replacement products
Cross-category recommendations
Dynamic bundling

Built For Shopify Brands

Works across every Shopify vertical, automatically.

Whether you sell skincare, supplements, pet products, apparel, coffee, consumables, or subscription products, the AI recommendation engine adapts to your catalog and customer journey automatically.

Shopify compatible

Native to how Shopify storefronts work.

Product catalog aware

Reads your catalog structure automatically.

Subscription-aware

Works alongside Recharge, Skio, Stay, and others.

Real-time recommendations

Responds to customer context as it happens.

Reduces support workload

Fewer product questions routed to your team.

Increases AOV automatically

No extra staff or manual rules to maintain.

Why This Works

Why customers respond better to conversational recommendations.

Customers are more likely to purchase when a recommendation feels like it came from someone who actually knows them — not from an algorithm that noticed someone else bought both items.

Feels helpful

Recommendations that answer what the customer actually asked.

Feels contextual

References what they bought, not what's trending site-wide.

Feels personalized

Adapts to skin type, dietary needs, pet breed, lifestyle.

Feels educational

Explains why a product fits — not just that it exists.

Feels natural

Like asking a knowledgeable store associate, not a pop-up.

This AI acts more like an expert shopping assistant than a recommendation widget.

AI Recommendation Engine

Turn customer conversations into higher order value.

AI-powered recommendations that understand customer context and drive smarter conversions automatically.