AI for Retail

AI for Retail That
Drives Real Revenue

Retail AI is not about technology — it is about revenue, margin, and customer loyalty. We build AI systems that personalise at scale, forecast demand accurately, price dynamically, and resolve customer queries instantly — producing measurable business outcomes, not dashboards.

Personalisation at scale Demand forecasting Dynamic pricing
27%
AOV Increase Typical
4.2%
Demand Forecast MAPE
98%
Client Satisfaction
AI for Retail Capabilities
Enterprise-grade
Personalised Recommendation Engines95%
AI Demand & Inventory Forecasting92%
Visual Product Search90%
Dynamic Pricing AI88%
Recommend
Forecast
Search
Price
🛍️ Retail AI
CanadaHVACfoot-logorakta-logobekn-logologo_modicumArcelorMittalHindustan_Unilever_Logo.svgMotorola LogoUnlistedkart logoArvest Bank LogoSaudi Irrigation OrganizationAurobindo PharmaWHO (2)L&T (2)FinoFarewayChromaBosch (2)
CanadaHVACfoot-logorakta-logobekn-logologo_modicumArcelorMittalHindustan_Unilever_Logo.svgMotorola LogoUnlistedkart logoArvest Bank LogoSaudi Irrigation OrganizationAurobindo PharmaWHO (2)L&T (2)FinoFarewayChromaBosch (2)
What's Included

AI for Retail, End to End

End-to-end capability — from strategy and build to integration, monitoring, and ongoing support.

🎯

Personalised Recommendation Engine

Collaborative filtering, content-based, and deep learning hybrid recommenders — personalising product discovery, email, and homepage for every customer in real time.

📦

Demand & Inventory Forecasting

LSTM and gradient boosting forecasting models at SKU, category, and store level — reducing overstock and stockouts while optimising procurement and replenishment cycles.

🔍

Visual Product Search

Computer vision-powered visual search — customers search by image, get exact and similar matches across millions of SKUs in under 200ms.

💰

Dynamic Pricing AI

Real-time pricing models that optimise margins while staying competitive — factoring in demand signals, inventory levels, competitor prices, and customer segments.

🤖

AI Shopping Assistants

LLM-powered shopping chatbots that guide product discovery, answer questions, track orders, and recover abandoned carts — across web, WhatsApp, and app.

😊

Customer Sentiment Intelligence

NLP pipelines analysing product reviews, social media, and support tickets — providing granular sentiment signals that feed product, marketing, and merchandising decisions.

How We Work

Our Engagement Process

A disciplined, outcome-focused approach from first call to go-live.

  1. 1

    Data Audit & Use Case Prioritisation

    Assess your customer data, transaction history, and product catalogue — and identify the AI use cases with highest revenue impact.

  2. 2

    Model Development & A/B Testing

    Build AI models with rigorous A/B testing infrastructure — measuring revenue impact, not just model accuracy.

  3. 3

    Real-time Serving Infrastructure

    Build low-latency prediction APIs and feature stores that serve personalisation and pricing in real time at scale.

  4. 4

    Integration with Commerce Stack

    Integrate AI with your Shopify, Magento, SAP Commerce, or custom commerce platform — surfacing AI in product pages, search, and checkout.

  5. 5

    Revenue Attribution & Optimisation

    Monitor revenue attribution from AI features, run multivariate tests, and continuously optimise based on business outcomes.

Technology Stack

Tools & Frameworks We Master

A production-tested, vendor-agnostic stack built for enterprise security and compliance requirements.

Recommendation Systems

Matrix FactorisationTwo-Tower ModelsDLRMTransformers4RecLightFMSurprise

Forecasting

ProphetLSTMLightGBMN-BEATSTFTStatsforecast

Commerce Integrations

ShopifyMagentoSAP CommerceWooCommerceBigCommerceSalesforce Commerce

Infrastructure

PineconeRedisKafkaAWSDatabricksSnowflake
Real-World Impact

Use Cases by Industry

Production AI systems we have built across regulated, data-heavy industries.

E-commerce

Hybrid Recommendation Engine

Matrix factorisation + deep learning recommender for 2M+ SKU catalogue — 27% increase in AOV, 19% improvement in conversion rate.

Collaborative FilteringAWS
Fashion Retail

Visual Search Engine

ViT-based visual search across 5M+ fashion products — customers search by photo, sub-200ms response time, 35% increase in discovery engagement.

ViTFAISSFashion
Grocery

Demand Forecasting at Scale

Prophet + LSTM ensemble for 50,000 SKUs across 200 stores — 4.1% MAPE at weekly level, $2.3M annual reduction in waste and overstock.

ProphetLSTMGrocery
Marketplace

Dynamic Pricing System

Real-time pricing AI factoring demand, inventory, and competitor prices — improved margin by 8.3% while maintaining conversion rate.

MLPricingMarketplace
D2C Brand

AI Chatbot for Support & Sales

GPT-4o chatbot handling 8,000+ daily conversations — 74% resolved without agent, 23% conversion uplift on chat-assisted sessions.

GPT-4oRAGD2C
Department Store

Churn Prediction & Retention

Customer churn model with 89% precision — triggered personalised retention offers 45 days before predicted churn, saving $3.8M ARR.

Survival AnalysisCRMRetention
Client Voices

What Teams Say After Shipping with Us

Real results from teams who needed AI to work in production, not just in a demo.

AndolaSoft has been a valued partner providing excellent customer service. Issues with clients or troubleshooting are handled in a timely manner and positive resolution is always the outcome.
JK
Jim Kaplan
Founder, AuditNet
I got a recommendation on AndolaSoft. They are more than half the cost, they have a can-do attitude, and they are responsive, timely, and easy to work with.
CV
Caroline Van Sickle
Pretty in my Pocket, Atlanta GA
Andolasoft team is very hardworking, dedicated and professional that follows through with their goals. The technical leadership is also a superior value to any other developers.
ZN
Zeid Nasser
Editor-in-Chief, theCollegeDriver.com
FAQ

Frequently Asked Questions

With a proper A/B test, most clients see measurable revenue lift within 4–6 weeks of deploying a personalised recommendation engine. We build the A/B testing infrastructure alongside the model so you have clean revenue attribution from day one.

Ready to Add AI to Your Retail Operations?

Tell us your biggest revenue or operational challenge. We will show you exactly which AI system solves it and what return to expect.