MageTech AI Sales & Product Recommendation Engine

MTS AI
Commerce Assistant

AI-powered recommendations that increase conversion rates, boost Average Order Value, and deliver personalized shopping experiences — without expensive SaaS subscriptions.

🛒 Buy Now Explore Features
35%
Revenue Increase
<50ms
Response Time
7
AI Engines
5
Placement Zones
Why Customers Will Buy

Drive Revenue With
AI Intelligence

MTS AI Commerce Assistant delivers measurable business results by personalizing every step of the customer journey.

📈

Increases Conversion Rate

Personalized product recommendations guide customers to products they're most likely to buy, boosting conversion rates by up to 35%.

Revenue Growth
💰

Improves Average Order Value

Smart upsell and cross-sell suggestions increase cart size by recommending complementary and premium products.

AOV Boost
🌟

Personalized Shopping Experience

Every customer sees recommendations tailored to their browsing history, purchase behavior, and preferences.

Personalization
💰

AI Without SaaS Costs

Enterprise-grade AI recommendations without expensive third-party SaaS subscriptions. One extension, full control.

Cost Savings
Features

Every AI Engine
You Need

Nine powerful AI engines working together to surface the right product at the right time.

🔍

AI Product Recommendations

Vector embedding similarity search using OpenAI's text-embedding-3-small model. Find products that are semantically similar to any item.

Vector Search
🛒

Frequently Bought Together

Analyze purchase patterns to surface products that customers commonly buy together. Increases average order value.

Purchase Analytics
📈

Smart Upsell / Cross Sell

Intelligent upsell and cross-sell suggestions based on product relationships, customer preferences, and browsing behavior.

AI Powered
🧠

Customer Purchase Prediction

Machine learning-powered purchase prediction that anticipates customer intent and pre-loads relevant products.

ML Engine
🏠

Personalized Home Page

Dynamic homepage recommendations that adapt to each visitor's browsing history and purchase patterns.

Dynamic
📈

Dynamic Product Ranking

AI-driven product ranking that surfaces the most relevant items based on real-time customer behavior signals.

Ranking
🔎

AI Search Suggestions

Intelligent search suggestions that learn from customer behavior to improve search relevance and discovery.

Search AI
🌸

Seasonal Recommendations

Time-aware recommendations that adapt to seasons, holidays, and trending products automatically.

Seasonal
🌐

Multi-Store Support

Full support for Magento multi-store setups with independent configurations per store view.

Enterprise
How It Works

From Data to
Recommendations

A streamlined pipeline that transforms customer behavior into actionable product suggestions, all running asynchronously in the background.

01

Data Collection

Event observers silently capture product views, add-to-carts, purchases, and browsing patterns. Every interaction builds a richer customer profile.

observer → catalog_controller_product_view → trackEvent('view', $productId)
02

Embedding Generation

Cron jobs and message queues generate vector embeddings for products using OpenAI's text-embedding-3-small model. Stored in Redis for instant similarity lookups.

AiProcessor::generateEmbedding($productName . ' ' . $description)
03

AI Processing

Seven specialized engines compute recommendations using cosine similarity, purchase patterns, and customer preference profiles. Results are cached for instant delivery.

SimilarProductsEngine → computeCosineSimilarity($vectorA, $vectorB)
04

Delivery & Tracking

Recommendations are served via GraphQL, REST API, or block widgets. Real-time impression and click tracking feeds back into the analytics engine.

GraphQL: productRecommendations(placement: "homepage", limit: 6)
Admin Panel

Powerful Admin
Dashboard

Monitor recommendation performance, manage prompt templates, and configure AI settings from a single, intuitive admin interface.

MageTech
admin/magetech airecommendation/analytics/dashboard
📊 Dashboard
🔍 Recommendations
✎ Prompt Templates
📈 CTR Reports
💰 Conversions
⚙ AI Configuration
🚀 Cache Management
Recommendation Analytics
Impressions
248.5K
↑ 12.3% vs last month
Click Rate
8.7%
↑ 2.1% vs last month
Conversions
3,847
↑ 18.5% vs last month
Revenue Impact
$127.4K
↑ 24.2% vs last month
Architecture

Built for Enterprise

Service contracts, repository pattern, message queues, and GraphQL — built following Adobe Commerce best practices for maximum extensibility.

📦 Service Contracts

  • RecommendationRepositoryInterface
  • PromptTemplateRepositoryInterface
  • RecommendationAnalyticsRepositoryInterface
  • VectorEmbeddingRepositoryInterface
  • RecommendationServiceInterface
  • AiProcessorInterface

⚙ Engine Strategy Pattern

  • AbstractRecommendationEngine
  • FrequentlyBoughtTogetherEngine
  • CrossSellEngine
  • UpSellEngine
  • SimilarProductsEngine
  • PurchasePredictionEngine
  • DynamicWidgetEngine

🔁 Database Schema

  • magetech_ai_recommendation
  • magetech_ai_prompt_template
  • magetech_ai_recommendation_analytics
  • magetech_ai_vector_embedding
  • magetech_ai_customer_preference
  • magetech_ai_tracking_event

🚀 Async Processing

  • communication.xml (3 topics)
  • queue_consumer.xml
  • queue_publisher.xml
  • queue_topology.xml
  • 5 Cron Jobs
  • Redis Cache Layer

🔗 API Layer

  • GraphQL: productRecommendations
  • GraphQL: similarProducts
  • GraphQL: frequentlyBoughtTogether
  • GraphQL: trackRecommendationEvent
  • REST: /V1/magetech/recommendations
  • REST: /V1/magetech/tracking

💻 Frontend

  • 6 Layout XML files
  • 10 Luma PHTML templates
  • 3 Hyva Alpine.js templates
  • tracking.js + widget.js
  • Responsive CSS
  • requirejs-config.js
Performance

Blazing Fast

Every millisecond matters. Our extension is engineered for speed with Redis caching, async processing, and zero frontend impact.

⚡

Redis Cache Layer

Two-tier caching with Magento block cache for frontend and Redis object cache for AI results. Configurable TTL from 60s to 24h.

🔁

Message Queue Consumers

AI calls are processed asynchronously via RabbitMQ/AMQP. Embedding generation and recommendation refresh never block the frontend.

🕑

Cron Job Scheduling

Five automated cron jobs handle embedding generation, recommendation refresh, analytics aggregation, cache warmup, and data cleanup.

💡

Fallback Strategy

When AI is unavailable, the system gracefully falls back to rule-based recommendations. Zero downtime, always responsive.

🔒

Lazy Loading

Images use native lazy loading. Intersection Observer tracks impressions without performance overhead. No layout shift.

🚀

Zero Frontend Impact

Recommendations load via AJAX after page render. The page is never blocked waiting for AI processing or database queries.

Compatibility

Works With Your Stack

Fully compatible with Luma, Hyva, and PWA Studio. Built for Magento 2.4.7+ and PHP 8.2+.

🎨

Luma Theme

Full PHTML template support with responsive grid and carousel layouts.

Fully Supported
⚡

Hyva Theme

Alpine.js powered templates. No KnockoutJS dependency. Lightweight and fast.

Fully Supported
💻

PWA Studio

GraphQL-first API layer. All recommendation data queryable via custom queries.

Fully Supported
Purchase
MageTech

Ready to Boost
Your Revenue?

Deploy AI-powered recommendations in minutes. OpenAI integration, full admin control, and enterprise-grade performance.

✓ OpenAI Integration
✓ 7 AI Engines
✓ GraphQL + REST API
✓ Hyva Compatible
✓ Redis Cache
✓ Async Processing
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