In how we build
Assay, our session-scoring app, run in production on client stores - separating real buyers from noise so optimisation decisions start from what actually happens, not averages.
AI, data and optimisation
We use AI where it earns its keep: scoring real buyer sessions with Assay, drafting options our team still judges, and building internal capability so your people spend less time on reporting, product data, support, and ops busywork.
Three places it shows up
Assay, our session-scoring app, run in production on client stores - separating real buyers from noise so optimisation decisions start from what actually happens, not averages.
AI proposes; nearly 900 projects of experience decides. Every recommendation is filtered through what we have watched work - and fail - since 2011.
The next advantage in ecommerce is internal: teams using AI to optimise reporting, product data, support and operations. We build that capability into the businesses we work with.
Workflows for titles, attributes, categorisation, search data, and merchandising inputs.
Recurring reports from the right commerce data, plus triage that uses order and customer context.
Lightweight admin tools that connect Shopify, apps, docs, and team processes - with a human still in the loop.
How we start
Map manual workflows, data gaps, repeated decisions, and where Assay or automation would actually help.
Build a focused workflow with guardrails, review steps, and clear ownership.
Connect Shopify, apps, docs, reporting, and internal team processes.
Measure time saved, output quality, and where the next useful step is - not the next novelty.
AI and data
Send the workflow, data gap, team bottleneck, or optimisation problem. We will tell you what is worth improving.