AI personalisation engines, intelligent search, dynamic pricing, and demand forecasting - built specifically for commerce, not generic AI wrappers. Every model is trained on your data, your catalogue, and your customers.
Avg conversion uplift
Increase in AOV
Overstock reduction
Each capability is a production system - not a third-party widget. Trained on your data, integrated at your architecture level, and monitored after launch.
Real-time product recommendations driven by session behaviour, purchase history, and browsing patterns. Each visitor sees a personalised homepage, category page, and search result. Integrates at the API layer - works on any platform.
Semantic vector search that understands shopper intent, not just keywords. Typo-tolerant, synonym-aware, and personalised by shopper profile. “Smart casual birthday outfit” finds the right product even if none of those words appear in product data.
ML pricing models that adjust based on demand signals, inventory levels, competitor monitoring, and margin targets. Automated markdown recommendations clear slow-moving stock without manual intervention or margin destruction.
SKU-level demand prediction per channel, per region, and per season - reducing both stockout and overstock events. Integrated with your OMS to trigger automated replenishment orders when model confidence crosses your defined threshold.
Real-time transaction scoring trained on your specific order patterns - high fraud catch rate with a low false positive rate that avoids rejecting legitimate customers. Works alongside Stripe Radar or as a standalone layer.
LLM-powered assistant trained on your catalogue, policies, and order data - answers product questions, tracks orders, processes returns, and escalates complex issues. Reduces transactional CS volume by 40–60% within 90 days.
We assess your historical order data, product catalogue, and customer records to determine what AI models are viable and what data quality work is needed first. No AI on bad data.
We establish current conversion rate, AOV, search conversion, and stockout frequency before any AI is deployed. This is the number we’ll measure against - agreed with you before we build.
We build the AI model on your data and integrate it into your platform - at the API layer where possible, avoiding frontend-only solutions that can’t personalise server-rendered content.
We A/B test the AI against your baseline before full rollout - so you see the uplift before committing to a platform-wide deployment. Output: Validated uplift data
Models are monitored for drift and retrained on a schedule as your catalogue and customer base grows. Included in managed services or as a standalone MLOps arrangement.
Developed a Python/Laravel-based smart routing algorithm for a Swedish cold-chain logistics company, enabling precise route assignments for drivers and dispatchers - reducing delivery times and improving operational efficiency.
We’ll audit your current data and tell you exactly which AI capabilities will move the needle - and what’s needed to get there.
Book a commerce AI assessmentFirst conversation is always with a senior commerce architect - not a sales team. We’ll give you an honest assessment and a scoped proposal.
NDA available before any conversation - countersigned within 24 hours.