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Competitive Intelligence 2025 Fashion & Apparel

Fashion Insights

Show brands what competitors just put on the rack.

A fully spec'd competitive intelligence system for athletic and lifestyle apparel — one product photo in, structured market data out, designed to land inside the PLM rather than next to it.

< 1 wk Brief to working prototype
< 3 wks Full V1 spec & four-month roadmap
7 Competitor catalogs in dataset
5 Extension domains, 30+ modules spec'd

Competitive intelligence that runs at the speed of the market.

Design and merchandising teams in athletic and lifestyle apparel spend weeks assembling competitive sets by hand: combing competitor sites, screen-scraping product pages, eyeballing fabric blends, tracking colorways across price tiers. By the time the deck lands, the line has already moved.

We took the problem on directly: could AI compress that work to seconds, from one image, and land the answer inside the team's existing PLM workflow?

We prototyped it inside a week.

Project Garment Insights
Category Competitive Intelligence
Deliverable Intelligence API
Built 2025
Frame Rogue Agents Spec Work
Image in.
Market context out.

Built to land inside
the PLM.

Three constraints shaped the build.

One input. A product photo — on-body or standalone — is the only thing a designer should have to provide. No prompt engineering. No taxonomy selection up front. The photo is the prompt.

Real catalog data. Matches come from live competitor catalogs — Lululemon, Ten Thousand, Athleta, Fabletics, Gymshark, TLF, and mass-market — with style names, fabric composition, current pricing, and color variants attached.

PLM-native. The output lands as structured data inside the product lifecycle management workflow the team already uses — not as a PDF, not as a separate dashboard to log into.

That last constraint is the one most "AI for fashion" pitches skip. It's the one that decides whether the tool gets used.

Primary / 02

The Development Option Menu

V1 is the foundation. We spec'd four months of follow-on builds across five extension domains — so a partner brand can compose their own roadmap without a meeting to figure out what to fund next.

  • Customer Intelligence — reviews, sentiment scoring, buyer profile mapping
  • Market Intelligence — white-space analysis, trend gaps, seasonal opportunity mapping
  • Product Intelligence — color-name analysis, fabric benchmarking, silhouette matching
  • Operational Intelligence — stock tracking, price monitoring, supply chain signals
  • Workflow Enhancements — batch processing, competitor-launch alerts, deeper PLM hooks
Extension Domains

Customer Intelligence

Review aggregation, sentiment scoring, and customer profile mapping across the competitive set.

Market Intelligence

White-space analysis, trend gap identification, and seasonal opportunity mapping by category.

Product Intelligence

Color-name analysis, fabric performance benchmarking, silhouette matching, and cross-gender trend signals.

Operational Intelligence

Competitor stock-level tracking, dynamic price monitoring, and supply chain insight signals.

Workflow Enhancements

Batch processing for full seasonal collections, competitor-launch alerts, and deeper PLM hooks.

How a single garment photo becomes structured market intelligence.

Built to land inside the PLM, not next to it.

One product photo. That's the whole input.

On-body lifestyle shot or flat product shot — either works. Multi-piece detection automatically separates tops and bottoms for independent analysis.

No prompt engineering required. No taxonomy choice required up front. The system infers garment type, category, and gender cut from the image itself.

Input received
Product image
[ on-body or flat — either works ]
Top detected Bottom detected
Category → Active Type → Shorts Cut → Women's

Find the same garment, and its neighbors, across the competitive set.

Visual similarity search runs across live competitor catalogs — from premium to mass-market — so the brand sees where it sits in the price landscape, not just one slice of it.

Same-color matches surface first. Alternate colorways are surfaced to reveal trend gaps. Match confidence is visible per result, so the user can act on certainty, not vibes.

Competitor matches — live catalog
Lululemon
94%
Ten Thousand
87%
Gymshark
79%
Athleta
74%
Fabletics
68%
Alternate colorways surfaced

Every match becomes a row of decision-grade data.

Style name, fabric composition, current price, promotional status, size range, availability, and full color variant lists — normalized so cross-competitor comparison just works.

Named colors, not "blue." Cerulean Heather. All fields structured for PLM import without manual cleanup.

Output schema — per match
Style name Pace Breaker Short 7"
Fabric 87% Poly / 13% Lycra
Price $68 — promotional ↓ $58
Colors Cerulean Heather + 5 variants
Sizes XS / S / M / L / XL — in stock
Construction 4-way stretch, flatlock seam

Lands inside the workflow the team already uses.

REST API with token-based authentication. Output schema designed to map to standard PLM data models. Custom field mapping available so the brand's internal naming wins.

Webhook hooks for competitive launch alerts. On-prem deployment option for security-sensitive accounts. The integration is the product.

Integration architecture
Rest endpoint POST /garment-match
Authentication Bearer ●●●●●●●●●●●●
PLM endpoint Custom field mapping — brand schema
→ Webhook: competitor-launch alert → On-prem deployment available

Prototype in a week.
Roadmap in three.

Traditional competitive set assembly takes one to three weeks per category and is stale on delivery. The Garment Insights prototype was hand-built in days. The full V1 specification and five-domain extension roadmap were ready inside three weeks.

What that means for a partner brand: structured competitive data on your own catalog by the end of month one.

Traditional competitive set assembly 1–3 weeks/category

Manual screen-scraping. Stale on delivery.

Garment Insights Seconds per garment

Live catalog data. Structured for the PLM.

Spec work. Production-grade thinking.

Fashion Insights wasn't built for a demo. It was built the way we approach every brief — from the problem backward, with the integration question answered before the architecture question, and a clear path from V1 to a full extension roadmap.

From a standing start to a fully documented, deployable system design in under three weeks. That's the pace and the depth we bring to any brief — campaign systems, branded AI experiences, interactive activations, competitive intelligence tools.

  • Fully spec'd system from brief to deployable architecture in under three weeks
  • Integration-first design — the PLM question answered before the API was built
  • Five-domain extension framework developed alongside V1, not retrofitted
  • Production-grade thinking applied to a spec brief, in a category we'd never worked in before
What's next

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