Segments · Groups & enterprise
Many houses, one architecture.
A group does not have an AI problem twelve times. It has an architecture problem once, and twelve pilots that prove it.
The shape of the day, not the pitch.
A group runs brands that share almost nothing operationally and everything structurally: each has its own codes, calendar and supply base, and each is separately procuring AI tools from separately-persuaded vendors. Two years of that produces a dozen incompatible pilots, a dozen data-residency conversations, and no leverage from being a group at all. The thing a group can do that a single brand cannot is build the layer once - and the thing that stops it is that nobody owns the layer.
5 of the twelve, in the order they pay here.
Not all twelve, and not the same order as any other segment. The argument for each position is below it.
- 01LLM-Native Platform Build
Foundation · Build
First because the alternative is twelve procurements. A group is the one buyer for whom building is straightforwardly cheaper than licensing, and the only one that can amortise it.
- 02Agent Orchestration
Foundation · Build
Second. Multi-brand means multi-tenant, and the routing, isolation and cost-attribution decisions are the ones that are expensive to change later.
- 03AI Governance & Compliance
Frontier · Deploy
Third. At group scale the AI Act obligations are real rather than theoretical, and the audit lands on the architecture rather than on any one brand.
- 04Agent Enablement & Academy
Frontier · Deploy
Fourth, and it is the one groups skip. A platform nobody in the maisons knows how to use is a platform that gets worked around - and internal champions are what stop that.
- 05Fashion Context Layer
Foundation · Build
Fifth because it is per-brand rather than per-group. It has to be built twelve times, which is exactly why the twelve other layers should not be.
Brand-scoped data, or nothing gets signed
No maison will accept its archive being reachable from a sister brand, and no group CTO will accept twelve isolated stacks. Row-level isolation inside one architecture is the only shape that gets through both conversations, and it has to be there from the first commit rather than added.
Build.
Twelve weeks and up, in your infrastructure, IP transferred
Because a group buys leverage, and leverage means owning the layer rather than renting it twelve times.
Groups & enterprise, on McLeuker AI.
The consultancy installs the layer; the platform is where your team runs it afterwards. This is the same segment described from the product side, and it is where an engagement here ships to.
Open it on McLeuker AI ↗One company. Two front doors.
We are not advisers who read about agentic AI. We designed, built and operate McLeuker AI - a multi-agent platform for fashion, running in production. That is where the consulting comes from: every recommendation is something we have already had to make work.
McLeuker
LLM and agentic AI expertise for fashion. We diagnose where agents belong in your operation, design the workflow, and install it alongside your team.
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McLeuker AI
The agentic AI platform we built and run for fashion brands. Your engagement ships onto it, loaded with your brand context.
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Four weeks, fixed fee, and a ranked map of what is worth automating in it — including what is not.