Services

AI

Automate repeatable workflows, enrich product data, and build intelligent integrations that cut manual overhead and speed up decisions.

Senior engineers only, no subcontractors

Most “AI for commerce” pitches are vague. Ours isn’t — we apply it to the specific, unglamorous jobs that eat the most time in real commerce operations: enriching product data, catching data-quality issues before customers do, and automating the manual steps between systems that nobody enjoys doing by hand.

What this looks like in practice

Four concrete jobs AI is already doing well in commerce operations — not a vague transformation pitch.

Data & Content

  • Product data enrichment — auto-generating and improving descriptions, attributes, and categorisation inside your PIM/DAM, so a catalogue of thousands of SKUs doesn’t need thousands of manual edits.
  • Content at scale — drafting first-pass product copy, alt text, and metadata for a human to review and refine, rather than starting from a blank page for every SKU.

Automation & Integration

  • Workflow automation — triaging and pre-processing repetitive tasks (order queries, catalogue updates, data matching) so your team spends time on judgement calls, not data entry.
  • Smarter integrations — AI-assisted data mapping when connecting systems that don’t share a common schema, cutting the manual mapping work in every integration project.

Where this fits

Every one of these applies AI to a problem inside a commerce stack we already know — Adobe Commerce, Shopify, WooCommerce, WordPress, or Pimcore — rather than treating AI as a bolt-on side project.

Our approach

We're a small, senior team deliberately expanding into AI-powered commerce tooling — applying the same platform depth and engineering rigor we've built over 15 years to this newer capability. We'll always tell you plainly where a project sits on that curve before you commit budget to it.

How we work

A process built around your outcomes, not our convenience.

1

Discovery

We learn your business, tech stack, and goals before writing a single line of code.

2

Architecture

We design the right technical approach — platform, integrations, data model.

3

Build

Iterative delivery with regular client-facing reviews. No black-box sprints.

4

Launch

Controlled go-live with performance baselining, monitoring, and a clear support plan.

5

Retain & Optimise

Ongoing retainer support, technical leadership, and iterative improvements.