AI for Fashion · The horizontal practice

Agentic AI inside every part of your fashion operation.

Product, merchandising, sourcing, marketing, customer ops — every workflow has decisions made many times, against rich context, under time pressure. We wire 22+ fashion-native agents into the cadence your team already runs, in 30 days, with full systems integration into your PLM, ERP, PIM, and DAM.

22+
Fashion-native agents
Tuned, not wrapped
30 days
Diagnose to operating
4 weeks · one phase per week
12+
Systems we integrate with
PLM · ERP · PIM · DAM · Commerce
6
Operating domains covered
Sourcing · Sustainability · Market · Brand · China · Cross-pillar
The one problem we solve

Generic AI tools don't speak fashion.

The pain

Your BOMs, suppliers, certifications, regulations, channels, and seasonal cadence sit outside any agent's context.

The result is predictable: marketing copilots produce claim-language legal cannot defend; supplier-search tools surface mills with expired certs; sustainability tools score the wrong CO₂e because they do not see the BOM; merchandising tools recommend pricing the competitor set already abandoned. Every output requires manual reconciliation — and the team that was supposed to be freed up is now reconciling outputs.

Where it breaks down every week

Five places generic AI will not survive a season.

No fashion context
Generic copilots have no idea what GOTS, LWG, EUDR, RWS mean — every output needs manual reconciliation.
Tools in silos
Marketing has theirs, buying has theirs, sourcing has theirs. Outputs do not reconcile and brand voice drifts.
No source-linked output
Claims with no evidence. Scores with no methodology. Recommendations with no provenance trail.
No system integration
AI lives in a sidebar tab; PLM, ERP, PIM, DAM live somewhere else. Manual data exchange every time.
Wrong cadence
Tools optimise for one-off tasks; fashion runs on seasons, drops, and disclosure cycles. The cadence misses every time.
Why us

Three things that make agents speak fashion.

We are not a generalist AI consultancy with a fashion deck. We built the platform, we know the operation, and we cover EU + Greater China end-to-end.
01
Agentic platform we built
22+ fashion-native agents on our proprietary McLeuker AI platform — a system we built, not a thin wrapper over someone else’s chatbot. Multi-model, multi-agent, streaming SSE, RLS-scoped.
  • 22+ agents pre-built and tuned
  • Multi-LLM with provider failover
  • Brand-context layer at the centre
  • Audit-ready provenance per output
02
Fashion knowledge baked in
BOMs, certifications (GOTS, OEKO-TEX, LWG, GRS, bluesign, RWS), regulations (CSRD, ESPR, AGEC, EUDR, GACC, PIPL), wholesale calendars, retail concession economics — at config-level, not retrofit.
  • Eight EU + APAC regulations covered
  • Tier-1 mill + tannery intelligence
  • Higg / PEF / DPP infrastructure
  • Fashion vocabulary at agent level
03
EU + Greater China depth
Tmall, JD, Douyin, Xiaohongshu, GACC, PIPL, GB textile standards, CNIPA — your APAC playbook is bilingual from day 1, native-reviewed in Shanghai and Hong Kong.
  • China entry · 30-day playbook
  • 4 marketplaces · 2 search engines
  • Mandarin + English deliverables
  • Native-review partners on call
The agent library

22+ agents, six operating domains.

Every agent is fashion-native — tuned to the data, the vocabulary, and the regulatory cadence of the operating domain it serves. Not a generic chatbot with a wrapper.
Sourcing & Supply
Supplier discovery
Cert verification
Risk monitoring
MOQ matching
Outreach drafting
BOM cost
Sustainability
Eco-design
Claims drafting
DPP generation
CSRD assembly
Market Entry
Competitor radar
Channel matrix
Pricing model
Regulatory map
Brand Strategy
Brand DNA
Persona generator
Tone-of-voice review
Localisation
China Operations
Tmall/JD/Douyin/RED scan
Chinese naming
Baidu + RED SEO
KOL/KOC shortlist
Cross-pillar
Brand context loader
Routing copilot
Evidence vault
Streaming cards
Systems we integrate with

The agent reads your existing stack.

We do not ask your team to leave the systems of record. The agentic layer reads from and writes to PLM, ERP, PIM, DAM, commerce, and marketplace APIs — your team continues to work where they work today.
PLM
Centric
PLM
Backbone
PLM
K3
ERP
NetSuite
ERP
SAP
PIM
Akeneo
PIM
Salsify
DAM
Bynder
DAM
Cloudinary
Commerce
Shopify
Commerce
Centra
Marketplace
Tmall API
Custom PLM / ERP / commerce integrations available — we have shipped against in-house systems built on top of Postgres, MySQL, MongoDB, REST, GraphQL, and gRPC.
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 operating teams use, and after day 30 the workflow refreshes monthly so it stays current as collections launch and markets shift.
Wk 1
Days 1–7
Diagnose
Day 7 — agent live

Walk through your operating model.

Working sessions with the heads of product, merchandising, sourcing, marketing, and commercial. Map the workflows, the systems of record, the weekly and seasonal decisions. Mark the places where agentic AI changes the economics.

You ship
  • Operating-model map signed off
  • Top 2–4 highest-leverage workflows
  • Systems-of-record inventory
  • Brand-context dossier loaded into the agent
Wk 2
Days 8–14
Design
Day 14 — design v1

Architect the agentic workflow.

Pick the two to four highest-leverage workflows. Design the agents, the tools, the data hand-offs, the human checkpoints — live in the room with your operating leads.

You ship
  • Agent architecture v1
  • Tool registry + guardrails
  • Workflow handoff diagrams
  • Workspace UI walkthrough
Wk 3
Days 15–21
Deploy
Day 21 — team operating

Ship it inside McLeuker AI.

Configure the agents with your brand context, integrate PLM/ERP/PIM/DAM as needed, onboard your team in working sessions in their own operating rhythm.

You ship
  • Workspace handed over with logins
  • Core integrations live
  • Team onboarding sessions complete
  • First operating dashboard visible
Wk 4
Days 22–30
Operate
Day 30 — operating

Run the first business cycle through the workflow.

First product review, first supplier shortlist, first marketing push, first CX triage — all through the agent. Then move to the retained monthly cadence.

You ship
  • First operating cycle run live
  • KPI baseline captured
  • Monthly refresh cadence agreed
  • Quarterly strategy review scheduled
What we ship

Eight working surfaces across the operation.

01
Eco-design BOM scoring
Per-garment impact (CO₂e, water, chemistry) on every BOM line, MOQ-aware swap candidates, evidence linked.
Example output
"This tee scores eco-B; 3 swaps pull it to eco-A within MOQ 300 and drop landed cost €1.20."
02
Supplier discovery + verify
Tier-1 mill / tannery shortlists, certification verification live, MOQ + lead-time + price-band per row.
Example output
"6 PT mills shortlisted for organic jersey; 3 carry GOTS + GRS; one offers 800-m MOQ."
03
Competitor radar
Continuous scan of direct + adjacent competitors per market; positioning, RRP bands, channel footprint, sustainability posture.
Example output
"3 competitors moved RRP +12% on Tmall this quarter; your equivalent SKU is 18% below benchmark."
04
Claims drafting + review
Marketing claims drafted with linked evidence, live-site claim scan flags Green Claims drift before it ships.
Example output
"Hero claim 'made in Europe' true for 78% of SKUs; alternate phrasing recommended for full-line homepage."
05
PDP + ad-creative drafts
PDP copy, ad variants per channel, lifecycle email — all in your brand voice with claim guardrails.
Example output
"30 PDPs drafted in a single agent run; tone-consistency 0.94 vs brand voice baseline."
06
Demand + replenishment
SKU-level demand modelling, restock cadence recommendations, reconciled against supplier lead times.
Example output
"Crew Tee — Stone, M, L — projected stockout in 11 days; PO of 1,800 units recommended 6 weeks ahead."
07
CX triage + size signals
Support tickets triaged, returns drafted, size-fit signals fed back into product and merchandising.
Example output
"Sizing complaints on Style D-104 trending +22% — likely waist-grade shift between size 38 and 40."
08
Wholesale + retail prep
Buyer-facing briefs, line-sheet variants per account, retailer onboarding packs assembled.
Example output
"Buyer brief for Tomorrow Showroom: 12 styles, pricing model, sustainability claims pack ready."
What changes

From AI sidebar to AI inside the operation.

Without an agentic AI workflow
With McLeuker
Where AI lives
Sidebar tab · separate from systems
Inside PLM/ERP/PIM/DAM workflows
Brand context
Re-pasted into every prompt
Loaded once · read by every agent
Output reconciliation
Manual every time
Source-linked · evidence per claim
Voice consistency
Marketing drifts from product
One brand context · one voice
Operating cadence
One-off task tools
Seasonal · drop · disclosure cadence
Scale
One workflow at a time
2–4 workflows day 30 · all 6 domains by month 3
Built on the architecture we ship every day
McLeuker AI22+ agentsMulti-LLMPLM integrationERP integrationPIM integrationDAM integrationEU FrankfurtRLSSSE streamingMandarin + English
FAQ

Common questions.

Is McLeuker a vendor or a consultancy?+

A consultancy. McLeuker AI is the platform our consulting practice built and operates, and seats on it are self-serve at mcleukerai.com. What we sell is the installed tier — the platform wired into your operation with your context loaded, which is not something a checkout can do.

How do you handle the systems we already use?+

We integrate. The agentic AI layer reads from and writes to your PLM (Centric, Backbone, K3, custom), ERP (NetSuite, SAP), PIM (Akeneo, Salsify), and DAM (Bynder, Cloudinary). Your operating teams continue to work in their systems of record; the agentic layer sits alongside and removes the work that does not need a human.

Do we need an in-house AI team?+

No. The McLeuker partner team — fashion strategists, sustainability scientists, AI engineers — is the team you operate the engagement with. If you have an in-house AI function we work alongside it; if you do not, we are the function for the duration of the engagement and the retained cadence after.

How do you keep brand voice consistent across agents?+

Brand context is the centre of the workspace. DNA, tone-of-voice, claim guardrails, product taxonomy live in one place every agent reads from. When you update DNA in the workspace, the next agent run reflects it.

Which workflows ship in the first 30 days?+

Two to four — chosen during the diagnostic. Typically: supplier discovery + cert verification, eco-design BOM scoring, market-entry competitor radar, brand-tone review. Everything else lights up on the retained cadence.

Every capability

Every capability, and every category we install it in.

AI for fashion is the broad question. These twelve are the specific answers, grouped by how deep in the stack they sit - and every one of them is installed differently depending on the category you are in.

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 for fashion, running in production. 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

Bring agentic AI into your fashion operation.

Book a 30-minute diagnostic. We walk through your operating model, identify the 2–4 workflows where agentic AI changes the economics, and brief you on what your team would be operating from on day 30.