AI & Software for Retail and Commerce
Personalised at scale. Profitable at every touchpoint.
We help retailers and e-commerce companies build AI-powered personalisation, demand forecasting, inventory optimisation, and customer experience platforms that convert more visitors and retain more customers.
Industry challenges we solve
The real problems, not the ones that look good on slide decks.
Generic customer experiences
One-size-fits-all product recommendations and messaging fail to convert. Customers expect personalisation at every touchpoint.
Inventory and demand mismatch
Overstocking and stockouts cost retailers billions annually. Manual forecasting can't keep pace with SKU complexity or demand signals.
Cart abandonment and churn
Average e-commerce cart abandonment exceeds 70%. Identifying at-risk customers and intervening at the right moment requires ML.
Rising customer acquisition cost
CAC is increasing across all channels. Retailers need to extract more value from existing customers through better retention.
How we help
Proven solutions built on modern AI and software engineering, not off-the-shelf tools repackaged.
Personalisation Engine
Real-time product recommendations, personalised search ranking, and dynamic homepage content — driving 15–30% uplift in conversion.
Demand Forecasting
ML-driven demand forecasts at SKU/location level — reducing stockouts by 25% and overstock by 30% across the product catalogue.
Dynamic Pricing
AI pricing models that respond to competitor pricing, demand signals, inventory levels, and margin targets in real time.
Customer Lifetime Value Models
CLV segmentation and churn prediction that inform acquisition bidding, loyalty investment, and retention intervention.
Conversational Commerce
AI shopping assistants that handle product discovery, size/compatibility questions, and order tracking — reducing support volume.
Unified Commerce Data Platform
Single customer view from POS, e-commerce, loyalty, and marketing — enabling true omnichannel personalisation.
Results from the field
Concrete outcomes from real deployments, not illustrative scenarios.
23%
conversion uplift
Personalisation engine drives 23% conversion increase for fashion retailer
Real-time recommendation model replacing rule-based system. Tested via A/B framework before full rollout.
30%
stockout reduction
ML demand forecasting cuts stockouts across 500-store network
SKU-level forecasting model incorporating weather, events, and competitor pricing reduced stockouts by 30%.
18%
revenue increase
Dynamic pricing drives 18% revenue per visit increase for electronics retailer
AI pricing engine updated prices 4x daily based on competitor, inventory, and demand signals.
Technologies we deploy
Personalisation
ML
Commerce
Data
Related industries
Ready to make personalisation a competitive advantage?
Tell us your current stack and revenue goals — we'll scope the right solution.
No commitment to start · NDA available on request · Senior engineers only