AI for Retail

AI that turns every customer interaction into revenue and loyalty

From personalized product recommendations to dynamic pricing and demand forecasting — QuantPi builds AI systems that help retailers increase revenue, reduce waste, and deliver exceptional customer experiences across every channel.

32%
Revenue Uplift
25%
Less Markdown Waste
4.5×
Recommendation CTR
28%
Inventory Cost Reduction
Industry Expertise

AI-powered retail that anticipates customer needs before they do

Retail is drowning in data but starving for insight. Customer behavior signals, transaction histories, browsing patterns, social media sentiment, weather data, competitor pricing — the volume is overwhelming. The retailers who win are those who can synthesize these signals into real-time action.

QuantPi builds AI systems that connect your data dots: personalization engines that drive 32% revenue uplift, demand forecasting that reduces overstock by 25%, and pricing algorithms that maximize margin while maintaining price perception. All integrated with your existing commerce platform.

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Technology Stack
PythonPyTorchTensorFlowRedisElasticsearchKafkaSparkA/B TestingdbtSnowflake
Compliance & Certifications
GDPRCCPAPCI-DSSSOC2
Solutions

What we build for retail & e-commerce

01

Product Recommendation Engines

Deep learning recommendation models that combine collaborative filtering, content-based signals, and real-time browsing behavior. 4.5× higher click-through rates than rule-based systems.

02

Dynamic Pricing & Markdown Optimization

AI-driven pricing that optimizes across demand elasticity, competitor prices, inventory levels, and margin targets. Reduce markdown waste by 25% while maintaining brand perception.

03

Demand Forecasting & Replenishment

SKU-level demand forecasting incorporating seasonality, promotions, weather, events, and trend signals. Automated replenishment that maintains 99% availability with 28% less inventory.

04

Customer Segmentation & Lifetime Value

ML-powered micro-segmentation and CLV prediction that enables personalized marketing, loyalty programs, and retention campaigns with 40% better targeting accuracy.

05

Visual Search & Discovery

Computer vision models that let customers search by image, find visually similar products, and discover complementary items — increasing basket size by 18%.

06

Omnichannel Analytics

Unified customer analytics across online, in-store, mobile, and marketplace channels. Attribution modeling, journey mapping, and next-best-action recommendations.

Success Story

Proven results in retail & e-commerce

Personalization Engine for an Online Fashion Retailer

A mid-market fashion e-commerce company had generic product recommendations. We built a deep learning personalization engine that increased average order value by 23% and recommendation click-through rates by 340%.

23%
AOV Increase
340%
Recommendation CTR
$12M
Incremental Revenue
FAQ

Common questions about AI in retail & e-commerce

Our custom models outperform generic platform recommendations by 3-5× in CTR and 2-3× in conversion because they are trained on your specific customer behavior patterns.

Yes. We support Shopify, Magento, Salesforce Commerce Cloud, SAP Commerce, and custom platforms via API integration.

Models show measurable improvement within 2-4 weeks of deployment as they learn from real customer interactions. Performance compounds over time with more data.

All personalization is GDPR-compliant with consent management, data minimization, and right-to-deletion support. We can run models on anonymized data without sacrificing quality.

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Ready to transform your retail & e-commerce operations with AI?

Start with a technical conversation. No pitch decks, no pressure — just a discussion about what’s possible for your industry.