AI Platform Engineering
AI inside the store you already run, from search to checkout.
We engineer AI into the store you already run: search that understands what a shopper means, an assistant that knows your catalogue and your policies, product content your team approves before it goes live, and a checkout AI agents can use.
Each feature is wired into the catalogue, cart and order systems you already run, and every release is tested against your own cases before a shopper sees it.
linen outfit for a summer wedding, with a yellow bag
Relaxed linen shirt
In stock in your size
Top-handle bag, saffron
Matches your search
White chunky sneaker
Seen in your photo
Summer fragrance
Often bought together
A shopper's sentence becomes the right shortlist, ranked for relevance, stock and your merchandising rules.
Answers from your catalogue, policies and orders, and hands over to your team when it should.
Structured top-handle bag in crocodile-embossed leather, with a silver clasp and a detachable strap.
Titles, descriptions and attributes are drafted from your data and wait for a person before they go live.
Search, ranking and assistant changes are checked against your own cases before shoppers see them, and the last good release is one step back.
The pieces we build most often. Each one connects to your catalogue, inventory, orders and payments, and each one is judged on your own data.
Keyword and semantic search together, with autocomplete, typo and synonym handling, and ranking that respects stock, margin and merchandising rules. Shoppers can type the way they talk.
“Pairs with”, “complete the look” and returning-visitor shelves built from behaviour and catalogue data, with rules your merchandisers can read and override.
A shopper photographs something they like and gets the closest matches you sell, in stock and in their size.
A conversational assistant on your site and messaging channels that answers from your catalogue, policies and order data, acts within limits you set and hands over to your team.
Titles, descriptions, attributes and translations drafted from supplier data and images, checked against your style guide and approved by a person before publishing.
Review highlights and answers to product questions, grounded in what customers actually wrote, with the source one click away.
Try-on for apparel, eyewear and beauty built on your own product images, so shoppers can judge fit and shade before they buy.
Signals that flag risky orders and likely returns before dispatch, with the reason shown to the person who decides.
Store-level availability, sensible substitutions when an item runs out, and delivery promises your operations can keep.
Agentic commerce
Shoppers are starting to buy through assistants that search, compare and check out for them. Open standards for this are arriving from the large platforms and payment networks, among them Google's Universal Commerce Protocol and the Agentic Commerce Protocol from OpenAI and Stripe.
We make a store readable and buyable by those agents: a clean, structured catalogue, an MCP server over products, cart and orders, verified agent checkout, and the rules that decide what an agent may do.
Most stores start with one feature on one channel. We build it inside your stack, prove it on your data and hand it to your team.
A short readiness sprint in your catalogue, analytics and order data to choose the first feature and agree how it will be judged.
Engineers work in your repositories and your cloud, wiring the feature into the catalogue, search, cart and order systems you already run.
We test on your own cases before launch, then release to a share of traffic and watch the measures you chose, with a rollback ready.
Runbooks, dashboards and a trained team. You own the code, the prompts and the evaluation set; we can stay on to run it if you want.
Tell us the platform you run and the feature you have in mind, and we will come back with a first view of how we would build it.