Software for retail and ecommerce, behind the storefront.

Most retailers have a perfectly good shop front. What breaks is everything behind it: stock that disagrees between channels, returns handled by hand, and a customer service inbox absorbing the consequences of both.

That is unglamorous work, which is precisely why it is usually still manual.

Where is my order, can I change it, and how do I return it typically account for the large majority of contacts. Handling those automatically, accurately, and with a clean escalation to a person, frees the team for the contacts that actually need judgement.

A store build or replatform sits in web development at £4,000 to £16,000 depending on catalogue size and integrations. Operational work behind the store, such as consolidating orders across channels or automating customer service, is application or custom AI work at £8,000 upward.

Where a rebuild risks the search visibility the current store has, that mapping work is part of the build rather than an extra, because losing rankings in a replatform is a planning failure.

Conversion rate by device, separated rather than averaged, because mobile usually carries the problem and the average hides it. Then Core Web Vitals measured on a real mid range phone rather than a desktop test.

Operationally, measure minutes per order spent on manual handling and the proportion of customer service contacts that are status enquiries. Both are direct automation targets and both are usually underestimated.

A 30-minute call to hear how the operation runs today, then a paid discovery step: interviews with the people doing the work, a look at the systems and data you already hold, and a ranked list of what would pay back, each with a price, a timeline and the monthly running cost once live. In most retailer engagements the first thing built is customer service automation for the questions that make up most of the inbox, where is my order, can I return this, is it in stock, because it is measurable inside a month and it funds the rest.

The build runs in weekly demos against your real inputs, including the messy ones. Integration with the systems you already run comes before anything clever, because that is where most of the value and most of the risk sits. Go-live is followed by handover: the code, the provider accounts and the credentials in your name, a runbook, documentation and a recorded walkthrough, plus a session for the people who will use it daily. Every price is fixed in writing before work starts, with a list of what is not included.

Consumer contract rules on returns, cancellation and delivery information, product safety and labelling obligations, and payment-security requirements set the boundaries. An AI that answers customer questions has to give accurate returns and delivery information, which means it reads from your policy and your order system rather than improvising, and it hands disputes, complaints and anything about a faulty product to a person. Customer data, order histories and card details carry the ordinary UK GDPR and payment-security duties, and marketing automation has to respect consent and the rules on electronic marketing.

Our published prices apply to every sector: an AI adoption audit at £2,500 to £6,000 fixed, credited in full against any build; a first AI implementation at £4,000 to £15,000; a custom AI system at £8,000 to £25,000; applications at £8,000 to £30,000 per phase; websites at £4,000 to £16,000; training from £1,200. For a retailer that usually means customer-service automation grounded in your order data as the first implementation, then product-content generation and stock or demand tooling as a custom system, with your commerce platform kept as the record.

The running cost is stated before go-live, per feature, and it scales with volume rather than headcount. From operating our own AI products, the model is rarely the expensive part; the channels around it, telephony and messaging, usually are, and a well-designed workflow sends most of its work to the small, cheap models. Every system we build reports cost per feature from day one and has spending ceilings that were tested by watching them fire.

Most of a retailer’s customer service is the same three questions, and answering them by hand is a cost that scales with orders. An assistant grounded in the order system, the returns policy and the stock feed answers them accurately and hands the rest to a person, and it does so on web chat, email and messaging from one source of truth. Product content is the second cost: descriptions, attributes and translations generated from the supplier data and approved before publishing. Margin is the third, where demand and stock tooling built on your own sales history beats the generic forecast in the platform.