Recommendations that lift average order value
Recommendation engines trained on your catalogue and your history for relevant cross-sell and up-sell on the home page, product page and checkout, not generic suggestions.
Applied AI · E-commerce
Applied AI for E-commerce
We embed AI in your store to sell more: recommendations that hit the mark, search that understands, product descriptions generated at scale, chatbots that close sales and demand forecasting that keeps stock in order.
THE CHALLENGE
The challenges of E-commerce
In e-commerce, every millisecond of load time and every campaign spike directly impact conversion and revenue. The software must be fast, resilient under spikes and well integrated with the rest of the commercial ecosystem.
- Traffic spikes during campaigns and seasonality
- Performance and load speed (conversion)
- Integrations (ERP, gateways, marketplaces)
- Scalability without runaway costs
- A smooth buying experience
How we help you
In e-commerce, AI justifies itself on a single metric: conversion. We don't want a decorative chatbot, we want the customer to find what they're looking for faster, the product page to sell on its own and stock to be where it needs to be. We apply recommendation, semantic search, content generation and demand forecasting directly to your catalogue and your buying behaviour, measuring the impact on average order value, conversion rate and returns. Business-focused AI, embedded in your platform, not in a demo.
Semantic search that understands the customer
Search that grasps intent and synonyms, tolerates typos and returns useful results even when the customer doesn't use your exact words. Fewer searches with no results, more sales.
Product descriptions generated at scale
Generation of descriptions, attributes and SEO copy for thousands of SKUs, consistent with your brand voice and ready to review, not to rewrite from scratch.
Sales chatbots and demand forecasting
Assistants that answer questions and guide customers to checkout, and forecasting models that anticipate demand to adjust stock and campaigns without stockouts or overstock.
WHAT YOU GAIN
Applied AI, results-driven
- Use cases prioritised by business impact
- Integrated with your data and your product, not an isolated chatbot
- Model cost and latency under control
- Evaluation and guardrails for reliable answers
- From prototype to production with judgement
FAQ
Frequently asked questions
Do the recommendations work with our real catalogue?
Yes. We train the models on your catalogue, your purchase history and your browsing behaviour, not on generic data. That makes the suggestions relevant, and we measure their impact on conversion and average order value.
Does semantic search replace our current search engine?
It can replace or complement it. We integrate it into your platform so it understands intent and synonyms, reduces searches with no results and increases conversion from search, measuring before and after.
Can I generate product descriptions without losing the brand voice?
Yes. We configure generation with your style guide and your attributes, and leave a review flow in place. You generate thousands of consistent, SEO-optimised descriptions at scale, and your team just supervises.
How do you measure that AI increases sales and not just spend?
We define the business metrics before we start —conversion, average order value, returns, stockouts— and we control model cost and latency. If a use case doesn't add measurable value, we don't take it to production.
Will AI actually work for my case or is it just a demo?
We start from the business problem, not the technology. If a use case doesn't deliver measurable value, we'll tell you. We only take to production what justifies it.
Do you use your own models or third-party ones?
Both, as appropriate: commercial models via API to move fast, and open or fine-tuned models when cost, privacy or latency demand it.
Shall we build something that scales, together?
Tell us about your project. We'll get back to you with a concrete plan and a senior team — not a generic quote.