Agentic AI Strategy · The master practice

Ship agentic AI inside your fashion operation in 30 days, not in a 6-month roadmap.

Your board has asked for an AI roadmap. Vendors are pitching point tools. Procurement is sceptical. Operations are stretched. We compress that into a four-week sprint — Diagnose · Design · Deploy · Operate, one week each — and ship the agentic workflow onto McLeuker AI, our proprietary platform, or as a custom build inside your stack.

30 days
Diagnose to operating
4 weeks · one phase per week
Multi
Model orchestration
Per-task routing · provider failover
22+
Fashion-native agents
Pre-built · tuned to your brand
EU
Default data residency
Frankfurt · RLS · DPA on file
The one problem we solve

You have the agentic-AI mandate. You don't have the platform team to ship it.

The pain

Boards want an AI roadmap. Vendors sell point tools. Internal teams have day jobs. Pilots stall.

Generic AI copilots don't speak fashion vocabulary, BOMs, certifications, or the EU + APAC regulatory cadence. Internal teams cannot evaluate vendors, write prompts, and build agentic workflows on top of seasonal launches and CSRD prep. Procurement and legal need provenance, audit trails, and data-residency guarantees that off-the-shelf tools cannot offer. The result: more vendor logins than business outcomes, and a stalled adoption that the next budget cycle cannot defend.

Where it breaks down

Five places generic AI cannot reach.

No fashion context
Generic copilots have no idea what GOTS, LWG, EUDR, GACC, or 38W denim mean — they cannot make decisions in your operation.
Tools in silos
Marketing has theirs, buying has theirs, sourcing has theirs. Outputs do not reconcile.
No audit trail
Every claim, every score, every recommendation needs source-linked provenance. Off-the-shelf tools do not provide it.
No platform team
Building a multi-agent, multi-LLM platform requires senior engineering capacity that fashion brands do not have on staff.
Procurement & legal block
Data residency, RLS, DPA, sub-processor lists, EU AI Act readiness — most vendors fail one of these in week 1.
Why us

Three things almost no other firm brings to the room.

We are the rare practice that has (1) built a multi-agent platform in production, (2) deep fashion-domain operating knowledge, and (3) operated end-to-end across EU and Greater China. Most firms have one. A few have two. Almost none have all three.
01
We built the agentic platform
McLeuker AI is our proprietary multi-agent platform — 22+ fashion-native agents, multi-model orchestration with provider failover, streaming SSE UI, brand-scoped data layer with RLS. We ship onto it; we can also build the same architecture inside your stack.
  • 22+ agents pre-built and tuned
  • Multi-LLM with provider failover
  • EU-Frankfurt residency by default
  • Full IP transfer track available
02
We know fashion operations
BOMs, mills, tanneries, certifications (GOTS, OEKO-TEX, LWG, GRS, bluesign), wholesale calendars, retail concession economics, CSRD / ESPR / AGEC / EUDR — the agent talks the language because we built it that way.
  • Eight EU + APAC regulations covered
  • Tier-1 mill + tannery intelligence
  • Higg / PEF / DPP infrastructure
  • Fashion vocabulary at agent level
03
We operate EU + Greater China
Most agentic AI firms focus on the US. We operate end-to-end in the EU and Mainland China — Tmall, Douyin, Xiaohongshu, GACC, PIPL, Mandarin agent prompts. Your APAC playbook is bilingual from day 1.
  • China entry · 30-day playbook
  • Tmall · JD · Douyin · Xiaohongshu
  • PIPL · GACC · GB regulatory map
  • Mandarin + English deliverables
The architecture

The stack we ship, every layer.

What you get is not a chatbot — it is an operating layer. UI, agents, LLMs, tools, API, database, residency. Every layer is brand-scoped to you and audit-trailed end to end.
UI
Streaming card UI · ⌘K copilot · Mandarin & English
CardsStreaming⌘KEN/CN
AGT
Multi-agent framework · 22+ fashion-native agents
SourcingSustainabilityMarketBrandChina
LLM
Multi-LLM orchestration with provider failover
Per-task routingReasoning chainStandard chainFailoverCost-aware
TLS
Tool registry · web search · scrapers · supplier DB
Live web researchBrowser automationSupplier DBPLM/ERPSix-provider fallback
API
Bun · TypeScript · SSE streaming · Vercel + Railway
BunTypeScriptSSEVercelRailway
DB
PostgreSQL · Row-Level Security · brand-scoped retrieval
PostgreSQLRLSpgvectorEU-Frankfurt
30-day ship · one month from brief to launch

Four weeks. Four phases. Operating.

Diagnose · Design · Deploy · Operate, one week each. Every week ships defined output your team operates from. After day 30, we convert into a retained monthly refresh cadence.
Wk 1
Days 1–7
Diagnose
Day 7 — agent live

Map where agentic AI fits in your operation.

Working sessions with the heads of product, sourcing, sustainability, marketing, and commercial. Document the workflows, the systems of record, the regulatory load — and the decisions where agentic AI changes the economics. Brand-context dossier loaded into the agent on day 7.

You ship
  • Operating-model map signed off
  • Top 3–5 agentic intervention points
  • Systems-of-record inventory (PLM/ERP/PIM/DAM)
  • Brand-context dossier loaded into the agent
Wk 2
Days 8–14
Design
Day 14 — design v1

Architect the agentic workflow for your business.

Run the agent in working sessions — agents, tools, data hand-offs, human checkpoints — sized to your team and your governance bar. Your leads edit in the room.

You ship
  • Agent architecture v1
  • Tool registry + guardrails
  • Data flow + RLS model
  • Workspace UI walkthrough
Wk 3
Days 15–21
Deploy
Day 21 — team operating

Ship it inside McLeuker AI (or build inside your stack).

Configure agents with your brand context, integrate PLM/ERP/PIM/DAM as needed, onboard your team in working sessions — not a one-hour training video.

You ship
  • Workspace handed over with logins
  • Agents configured with brand context
  • Core integrations live
  • Team onboarding sessions complete
Wk 4
Days 22–30
Operate
Day 30 — operating

Run the first business cycle through the workflow.

First product review, first supplier shortlist, first market scan — all through the agent, with the McLeuker partner alongside. Then we move to the retained monthly cadence.

You ship
  • First operating cycle run live
  • KPI baseline captured
  • Monthly refresh cadence agreed
  • Quarterly strategy review scheduled
Two engagement tracks

Ship onto our platform, or build inside yours.

Default deployment is McLeuker AI — fastest time-to-value, lowest TCO. If you need to own the stack (data residency, IP control, regulated environment), we build the same architecture inside your infrastructure with full IP transfer.
Track A · Default
Ship onto McLeuker AI
Our proprietary agentic AI platform for fashion. Pre-loaded with your brand context as part of the engagement.
  • 30 days from kickoff to operating
  • 22+ agents pre-built and tuned
  • EU data residency · RLS · DPA
  • Continuous platform updates included
  • Lower TCO · faster time-to-value
Track B · Build-partner
Build inside your stack
Same architectural blueprint, deployed inside your own infrastructure with full IP transfer at handover.
  • Multi-LLM orchestration · same as ours
  • Multi-agent framework · same as ours
  • Brand-scoped data layer with RLS
  • Streaming SSE UI · ⌘K copilot pattern
  • Full IP transfer · no vendor lock-in
What we ship

Eight working surfaces, day 30 in your hands.

Inside the workspace, every surface is brand-scoped, evidence-linked, and refreshable on demand. No PDFs. No vendor-locked exports.
01
Unified copilot · ⌘K
One conversational surface. Routes to the right agents and tools per question. Streaming SSE UI; cards, not walls of text.
"⌘K from anywhere — "plan SS27 China launch" routes to the China agent."
02
Brand context layer
Your DNA, BOMs, suppliers, certifications, prior playbooks held in one governed workspace with Row-Level Security.
"Every agent reads the same brand DNA — voice never drifts across channels."
03
22+ fashion-native agents
Sourcing, sustainability, market entry, brand, China, claims, DPP, supplier intelligence — agents that speak fashion.
""Score this BOM" → eco rating, swap candidates, supplier shortlist."
04
Tool registry
Live web research, supplier databases, PLM and ERP integrations — orchestrated under one chain with failover across six search providers.
""Verify Mill X GOTS cert" → live search → supplier DB → answer with the source attached."
05
Multi-model router
The right frontier model selected per task, with cost-aware routing and provider failover — a router we built and operate.
"Grounded citation, China-market reasoning and imagery each route differently — and none of it stops when a provider does."
06
Audit-ready provenance
Every tool call, every answer, every claim linked to its source. Auditor-ready, regulator-ready, retailer-ready.
"Every claim card carries the cert ID, audit date, and replay button."
07
Streaming card UI
Cards stream in as the agent reasons — supplier cards, claim cards, channel cards, product cards. No walls of text.
""Find PT mills for organic jersey" → supplier cards stream in with cert + lead time."
08
Retained operating cadence
Monthly working sessions, quarterly strategy reviews, continuous platform updates from the McLeuker partner team.
"Same partners brief to operate — no handoff to junior team."
What changes

From AI mandate to AI operation, dimension by dimension.

Without an agentic AI workflow
With McLeuker
Time to first value
6–12 months · pilots stall · vendor RFPs
30 days · operating workspace handed over
Fashion vocabulary
Generic AI does not know GOTS, LWG, EUDR
Agents speak fashion at config-level
Tool sprawl
6–10 vendor logins · no reconciliation
One workspace · one brand context
Provenance
Outputs without source links
Every output linked to evidence record
LLM dependency
Single-vendor risk · outage = stop
Multi-LLM with failover · always on
Procurement / legal posture
DPA, residency, AI Act readiness gaps
EU residency · RLS · DPA · audit log
Total cost
Per-seat SaaS sprawl + integration fees
Engagement + platform · single line item
The benefits to your business

What clients walk away with, day 30 onward.

30 days
To operating
From kickoff to a working agentic workflow your team operates from. No 6-month roadmap.
−65%
Time on synthesis
Across the workflows we ship, your team spends 65% less time on synthesis-heavy work — freed for judgement.
5×
Decision speed
On the workflows we ship, decisions that took a week now take a day, against richer context.
100%
Source-linked outputs
Every recommendation, claim, and score linked to evidence. Audit-ready and regulator-ready by default.
Built on the architecture we ship every day
McLeuker AIBunTypeScriptPostgreSQLRow-Level SecuritySSE streamingVercelRailwayEU FrankfurtMulti-model routingProvider failover
FAQ

Common questions.

Is this a tool sale, or a consulting engagement?+

A consulting engagement. McLeuker AI is the platform our consulting practice deploys as part of the engagement — it is not sold as a self-serve SaaS. You hire the practice, the practice deploys the platform inside your operation in 30 days.

Can you build an LLM-native platform inside our own infrastructure?+

Yes — that is our second engagement track. Same partner team, same architectural blueprint (multi-agent framework, multi-model orchestration with provider failover, brand-scoped data layer with RLS, streaming UI), deployed inside your stack with full IP transfer at handover.

Why route across models instead of standardising on one?+

Because different frontier models are strongest at different jobs — long-horizon agentic reasoning, live signals, grounded citation, imagery, Chinese-language work — and because providers go down. We built the router that picks per step, with cost-aware selection and failover, so the operation never stops when one vendor does. Which models sit behind it is our engineering decision, revisited as the field moves; you get the capability and the guarantee, not a dependency on any one vendor.

How is McLeuker different from a generalist AI consultancy?+

We work only with fashion brands and we have built the underlying agentic platform ourselves. Our recommendations are grounded in a system we can ship — across LLM strategy, frontend, backend, and database — in a domain we know.

Where does our data live?+

EU Frankfurt by default with Row-Level Security at the database layer and brand-scoped retrieval. For clients with strict residency needs we run a dedicated instance or build inside your own infrastructure. We sign the DPA before the diagnostic begins.

Is the 30-day ship really realistic?+

Yes. Diagnose · Design · Deploy · Operate, one week each. It works because the platform is already built — your engagement loads your brand context onto agents that already know the fashion domain. After day 30 we move to a retained monthly cadence.

McLeuker · 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 running in production for fashion brands. That is where the consulting comes from: every recommendation is something we have already had to make work.

01The consultancyYou are here

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.

Book a consulting call

mcleuker.com

02The platform

McLeuker AI

The agentic AI platform we built and run for fashion brands. Your engagement ships onto it, loaded with your brand context.

Open McLeuker AI

mcleukerai.com

Book a 30-minute agentic AI diagnostic.

We walk through where agentic AI fits in your operation, what a McLeuker engagement would look like, and what your team would be operating from on day 30.