Ecommerce and retail AI that runs the operation behind the store

AI is used in ecommerce and retail to personalise product recommendations, forecast demand by SKU, automate order routing and fulfilment, answer customer questions, track competitor prices and spot patterns in sales and returns data. The most useful systems are trained on the retailer’s own history and connected to its store, marketplaces and back-office software, so their output turns into action rather than a separate report.

We do both, but as separate services. This page covers the technology behind the store: forecasting, recommendations, order automation, integrations, support AI and price monitoring. For the storefront itself, see our ecommerce website development, Shopify development and dropshipping store setup services. Many retailers keep their existing store and add these systems around it, which is usually faster than rebuilding.

It depends on the system, and every project gets a written quote after a free scoping call. As typical ranges from our service pages: a single automated workflow costs £2,000–£5,000 under business automation, a focused AI support chatbot £5,000–£15,000 under AI chatbot development, a focused forecasting or recommendation model £8,000–£25,000 under machine learning, and a managed competitor price feed £200–£2,000 a month under web scraping.

A single order or stock workflow typically takes one to two weeks, and multi-system automation three to six weeks. A focused customer-support chatbot is typically two to four weeks. Forecasting and recommendation models typically take six to sixteen weeks, because the sales data has to be cleaned and the model tested against past results. You get an estimated timeline with the written quote.

Yes. We build two-way integrations that sync products, stock, orders, customers and invoices between Shopify or WooCommerce and ERPs such as NetSuite or Odoo, accounting tools such as Xero and QuickBooks, and warehouse or 3PL systems. Where a platform offers an API we use it; where it only accepts files or email, we automate those too, with logging so failed syncs are visible.

Yes. We build a central order and stock service that pulls orders from each channel, updates one source of truth for inventory and pushes the correct stock level back to Shopify, WooCommerce, Amazon, eBay and other marketplaces. Safety buffers and channel rules are configurable, and mismatches are flagged for review instead of silently overselling.

Demand forecasting uses your historical sales, seasonality, promotions, stock-outs and supplier lead times to predict how much of each product will sell in the coming weeks. The forecast then feeds reorder suggestions or draft purchase orders that your buyers approve. It works best with at least one full year of sales history, so seasonal patterns can be learned rather than guessed.

Collecting publicly available prices is common practice, but the legal position depends on the website’s terms, the jurisdiction and whether personal data is involved. We only collect public product data, respect rate limits and avoid anything behind a login. We will explain the practical limits during scoping, but you should take your own legal advice on how you use competitor data.

It should not, because a well-built support assistant answers only from your own policies, product data and live order information, and hands over to a person when it is unsure or the question falls outside what it knows. We test it against real customer questions before launch, log every conversation for review, and set clear rules for refunds, complaints and anything that needs human judgement.

Not always. Stores with limited history can start with rules and content-based recommendations that use product attributes such as category, colour or price. As purchase and browsing data builds up, a collaborative model that learns from what similar shoppers bought can replace or blend with those rules. We check your data during scoping and recommend the approach it can support.

Yes. SpiderHunts Technologies works remotely with ecommerce and retail businesses in the UK, USA, Canada, Europe, Australia and elsewhere. We handle multi-currency and multi-market data, and build with GDPR safeguards for customer data. Responsibility for regulatory compliance stays with the retailer, and we design systems to support it.