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Fashion & Apparel · AI Use Cases

AI That Understands Fashion Wholesale. Not Just Data.

FIRE AI is not a chatbot. It is not a search engine with a language model on top. It is a system trained on your wholesale data — your orders, your buyer behaviour, your content performance, your size patterns — that surfaces insights no human could assemble manually. And it gets smarter every season.

The Foundation

AI Without Connected Data Is Just Guessing

Every fashion brand talks about AI. Few have the data infrastructure to make it work. AI needs connected, structured, accumulated data. It needs to know what a buyer browsed on the portal, what the rep showed on the Sales App, what performed in the showroom, and what was ultimately ordered — all in one place.

That is exactly what FIRE provides. Every AI capability described on this page is powered by data that flows through FIRE Core — captured at the moment of interaction, connected to a unified buyer profile, and accumulated over seasons. The AI does not guess. It analyses what actually happened.

AI Capabilities

Six Ways AI Transforms Fashion Wholesale

Magic Finder

AI-Powered

Finds similar products based on product information and images. When a buyer loves a style that is out of stock or discontinued, the Magic Finder surfaces alternatives from the current collection — automatically, everywhere: topics, looks, catalogue, groups, and checkout.

Product Combinations
< 1sResponse Time

Co-Pilot Insights

Analytics AI

The Co-Pilot analyses all captured data and delivers actionable insights: which products are your best performers, which are underperforming, how content drives conversion, and what your order preparation should focus on. Evaluations by MPG, country, and key performance indicators.

5+Dashboard Views
Real-TimeAnalysis

Size Pattern Prediction

Order AI

Analyses order history per buyer and per category to suggest size distributions. When a returning buyer opens a new order, the size grid is pre-populated based on their historical pattern — adjusted for category and season. Less manual input, more accurate orders.

AutoPre-Fill
Per BuyerPersonalised

Best Performer Analysis

Sales AI

Top-selling badges on product tiles. Analysis by MPG, country, and other key indicators. A new filter lets sales reps instantly identify best performers and check whether any are missing from the current order. Optional, toggleable, activated when needed.

LiveBadges
MultiDimension

Content Performance AI

Marketing AI

Which intros are watched? Which capsules convert? Which lookbook styles drive orders? The Co-Pilot tracks content engagement — watchtime, conversion, drop-off — and highlights your top gainers and underperformers. Marketing decisions backed by selling data, not impressions.

WatchtimeTracked
ConversionMeasured

Order Preparation Intelligence

Planning AI

Before the season starts, the Co-Pilot identifies: best-performing products from the previous season, number of orders in preparation, order-to-customer ratios, and top-performing looks and capsules. Your sales team walks into the season with a data-backed plan, not a blank page.

Pre-SeasonInsights
DataBacked
Fashion-Specific

Where AI Makes the Biggest Difference in Fashion

Size Curve Optimisation

Fashion has a unique complexity: the same style in different markets needs different size distributions. AI learns from order history per buyer, per region, per category — and pre-fills grids that match reality, not assumptions.

Seasonal Carry-Over Intelligence

Which styles should return next season? Which colourways performed in which markets? AI analyses sell-through data alongside order data and content engagement to recommend the strongest carry-over selection.

Cross-Selling That Actually Works

Traditional cross-selling relies on manual rules. The Magic Finder uses product similarity based on images and attributes — so when a buyer adds a tailored trouser, the system suggests coordinating jackets and shirts that actually match.

Trade Fair Preparation

Before Pitti, before CIFF, before Première Vision — the Co-Pilot analyses which buyers are confirmed, what they ordered last time, which products are trending, and what your team should prioritise. Walk in prepared, not reactive.

Buyer Segmentation by Behaviour

Not all buyers are equal. AI segments by ordering pattern, channel preference, size consistency, reorder frequency, and content engagement. Your sales team knows who needs attention, who is growing, and who is at risk.

Content ROI Measurement

You invest heavily in lookbook photography, capsule stories, and campaign films. AI connects content engagement to actual orders — which creative investment drives revenue and which does not. Budget allocation backed by data.

Our Approach

AI That Assists, Not Replaces. Augments, Not Automates.

There is a misconception that AI in wholesale means replacing sales reps with algorithms. That is not what FIRE does. The best sales reps have decades of intuition, relationship depth, and market understanding that no system can replicate. What AI does is give them superpowers.

When a rep walks into a showroom appointment, the Co-Pilot has already analysed the buyer's last three seasons. It knows which categories grew, which sizes shifted, which content the buyer engaged with on the portal last week. The rep does not need to remember — the system remembers for them. They can focus on what humans do best: building relationships, reading the room, and closing the deal.

The same applies to marketing teams. They do not need AI to create their lookbooks. They need AI to tell them which lookbooks actually drove orders, which capsule stories held attention, and which creative investments delivered return. The Co-Pilot does not replace creative decisions — it informs them with data that was previously invisible.

This is the difference between AI as a gimmick and AI as a competitive advantage. Gimmick AI generates text and images. Competitive AI analyses your proprietary data and surfaces insights that only exist because you captured the interactions. Every season of captured data makes the AI more valuable. Every season without it is intelligence you can never recover.

AI Is Only as Good as the Data Behind It

FIRE captures the data. The AI turns it into decisions. The longer you capture, the smarter the system gets. Start now — the compounding has already begun for your competitors.

See AI in Action

Own Your Data. Learn From It. Use It With AI.

Trusted by Hugo Boss, Drykorn, LVMH, Bugatti Shoes, Micro Mobility, Mercedes, Binelli Group and 100+ leading brands worldwide.

FAQ

Frequently Asked Questions

The Co-Pilot is FIRE's AI layer. It analyses data from all channels and surfaces insights: best performers, content effectiveness, buyer behaviour patterns, and order preparation recommendations.
The Magic Finder identifies similar products based on product information and images. It extends the cross-selling wheel with AI-powered similarity matching across topics, looks, catalogues, and checkout.
The AI improves as data accumulates. From season one, basic patterns emerge. By season three, the system delivers predictive insights. The more you capture, the smarter it gets.
Typically 20 to 40 days from kickoff to live operation, including ERP integration.
No. The B2B Portal runs in any browser. No app, no download, no account setup.
Yes. FIRE integrates with all major ERP systems including SAP and Microsoft Dynamics.
Also available for
Beauty & Cosmetics Footwear Sports & Outdoor Jewellery & Watches
All Industries →
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Talk to Our Team

Tell us about your brand, your current B2B setup, and what you are looking to improve. We will show you exactly how FIRE works for your specific situation.

No generic demos. No slide decks. A real walkthrough with your products and your industry configuration.

What Happens Next

1
Discovery Call
Your products, channels, and systems.
2
Custom Demo
Platform configured for your industry.
3
Go Live
Connected to your ERP in 20–40 days.
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