AI consultancy for retail and consumer brands that starts with the P&L, not the tool. We find the use cases worth funding, build and run them with your team, and measure them in hours saved, margin and revenue.
AI ideas pile up, a few get trialled, and none can show a number in the P&L.
Without a consistent way to compare ideas, the business funds whichever one has the strongest sponsor, not the best return.
AI tools get bought, then sit unused because they don't fit how store, service and operations teams actually work.
Score every idea on commercial impact, feasibility and effort on the same terms, so you fund the few that move margin.
Trading reports, customer service, stock and availability, pricing and promotions: the places where retail data already exists and decisions repeat every week.
Agents draft and recommend; people approve anything customer-facing or financial. Read our guide to human-in-the-loop AI.
Set a baseline before launch and review after a few weeks: scale it, fix it or stop it. Then train your team to run and extend it.
Weekly channel, store and category reporting assembled automatically, with the exceptions flagged for a person to act on.
Incoming queries sorted, drafted and routed, so the team spends its time on the ones that need judgement.
Earlier warnings on availability gaps, promotions that aren't paying back and prices out of line, before they cost margin.
Offers and messages matched to what customers actually buy, so promotions reach the people they'll move.
We built the agents that took reporting and admin off the team's plate, and taught them to run it themselves.
A fast-growing skincare brand with a lean team spending hours each week on manual channel reporting, customer-service triage and creator-gifting admin — time that should have gone into growth.
Built AI agents to automate weekly channel performance reporting, customer-service triage and the creator-gifting pipeline, with human approval built into each workflow. Then ran a three-hour hands-on AI 101 programme so the team could operate and extend the tools without us.
Around five hours a week saved on reporting and automation, operational speed up roughly 10%, and a team that can now build on the tooling itself.
A major UK retail group had plenty of AI ideas but no way to tell which were worth funding. We built an AI idea evaluation framework scoring each idea on commercial impact, feasibility and effort, replacing ad hoc selection with a ranked, funded pipeline the business keeps using.
We pick the technology and AI initiatives that show up in your margin, not just your press release. Across that work, our team has delivered 21 initiatives and $10m in projected margin uplift. See how we build AI agents.
Mostly in four places: reporting and forecasting, customer service, personalised marketing and offers, and operations such as stock, pricing and promotions. The use cases that pay back fastest usually remove repetitive work or catch revenue and margin leaks earlier.
Score each one on commercial impact, feasibility and effort, on the same terms. We built this kind of AI idea evaluation framework for a major UK retail group, turning ad hoc idea selection into a ranked, funded pipeline.
A focused use case such as automated reporting or service triage can be live within weeks and measured against a baseline soon after. Bigger changes take longer, so we sequence quick wins first.
Yes. Agents draft and recommend; people approve anything that reaches a customer or moves money.
For Facetheory, a UK skincare brand, our AI agents saved around five hours a week and improved operational speed by roughly 10%. Across our technology and AI work, our team has delivered 21 initiatives and $10m in projected margin uplift.
Tell us what you've tried and what it cost. We'll tell you, straight, which use cases would move your margin. Or take the free AI readiness assessment.