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Give your catalog perspective — speak the language your shoppers use.

AI-powered catalog enrichment with expert oversight—delivering shopper-ready data that feeds search and SEO.

See How It Works Try 50 Images Free
Product image annotated with fashion categories and attributes
10–25%

Search-Driven Revenue

Search-Driven Revenue

Lift in revenue influenced by search

Shopper searches “quiet luxury blazer”

finds your relaxed-fit tailored blazer. That's revenue, not just traffic.

60-85%

Zero-Result Searches

Zero-Result Searches

Reduction from understanding shopper language

Customer searches “terracotta knit sweater”

we match it to your rust-colored cable knit, even though you tagged it Orange.

3-5x faster

Enrichment Speed

Enrichment Speed

24-hour SLA for standard catalogs

Upload 5,000 products today

AI enriches, experts verify, delivering enriched data back within 24 hours.

20-35%

Precise Product Matches

Precise Product Matches

Increase in long-tail and seasonal discoverability

“Black midi dress for work”

finds your tailored sheath dress — not every black dress in your catalog.

The Problem

Your shoppers can't find what you stock. And it's costing you revenue.

60% of searches return zero results – even when the products exist in your catalog – which means you're losing 18-24% of potential search-driven revenue to broken discovery.

Example

Shopper Searches

"cozy cable knit sweater"

Your System

0 results

Your Actual Inventory

73 matching SKUs

Every failed search is abandoned revenue.

This isn't just a data gap. It's a data and perspective gap.

Why this keeps happening

The context shoppers actually use is missing. Your catalog has basic data – category, color, material. But shoppers don't search that way. They search for:

  • Trends

    “Cottagecore,” “Quiet Luxury,” “Y2K”

  • Occasions

    “Date Night,” “Workwear,” “Vacation”

  • Moods

    “Romantic,” “Edgy,” “Minimal,” “Bold”

  • Style Signals

    “Relaxed fit,” “Structured,” “Flowy”

Our View

Fashion isn't a classification problem. It's a context problem.

Most systems identify objects. Fashion teams interpret meaning.

Generic AI sees: "dress"

Fashion teams see: "midi shirtdress with relaxed fit, desk-to-dinner versatility, quiet luxury aesthetic, effortless workwear styling"

The gap: AI sees objects. Fashion teams see context, trends, occasions, and mood.

The Solution Perspiq.ai – it closes this gap.
Fashion catalog imagery

The Shift

From object recognition to managed understanding

Generic AI output versus Perspiq.ai output — structured attributes and a rich vocabulary word cloud for a red qipao dress Try 50 Images Free

Why Perspiq.ai

Built for fashion retail, not generic AI

Most AI is trained on internet images. We're trained on real fashion catalogs—4,500+ categories, 900,000+ retail attributes from actual brand taxonomies.

What makes us different

Perspiq.ai

  • Deep expertise in AI driven product discovery
  • Trained on 900K+ retail attributes from real fashion catalogs
  • 50M+ assets enriched over two decades using human experts
  • Captures trends, occasions, moods (“quiet luxury,” “date night,” “effortless”)
  • Brand-safe tonality, descriptions sound like your brand
  • Proven operational bandwidth to handle client demands at scale, without delays
  • Works with your existing stack through API and Cloud integration

Fashion AI Alternatives

  • Trained on generic internet images
  • AI outputs dumped into your catalog—you clean up the mess
  • Basic attributes only (“dress,” “blue,” “cotton”)
  • Generic robot copy that sounds like Amazon
  • Requires months of training on your data
  • Platform replacement or heavy customization required
  • Limited deployments, unproven at catalog scale

The result: Better discovery → more findable products → higher revenue.

How It Works

From product image to enriched catalog

Pipeline: product image to enriched catalog

Capabilities by Outcome

One understanding layer, multiple business applications

Search & Discovery

Match natural language queries to products

  • Match natural language queries to products
  • Surface relevant results for long-tail searches
  • Reduce zero-result searches by 60-85%
  • Handle shopper language variations automatically

Example

Shopper searches “chunky cable knit sweater” → system matches textured pullovers, relaxed-fit knits, and cozy sweaters—not just items tagged “sweater”

Move the slider to see the Impact of our Enrichment

White Qipao
Your catalog today Perspiq Enriched Output

$
%

Revenue you could recover

+$0 / SKU

$0

Avg. $50 AOV · 2.2% base CVR

Conversion Rate Uplift

vs generic AI

+0.0%

Cart Completion Lift

fewer exits

+0.0%

Works with what you already have

Designed to layer into your existing stack

Commerce Platforms

Commerce Platforms

  • Shopify
  • Salesforce Commerce Cloud
  • BigCommerce
  • Adobe Commerce
Search Engines

Search Engines

  • Algolia
  • Elasticsearch
  • Coveo
  • Bloomreach
Data Pipelines

Data Pipelines

  • REST API
  • GraphQL
  • Webhooks
  • CSV/FTP
Workflow Tools

Workflow Tools

  • PIM Systems
  • DAM Tools
  • MDM Solutions
Don't see your platform? Talk to our Integration Team

Resources

Clear thinking on search, data, and trust

Aesthetic Search Is Now 25% of Fashion Queries — And Most Catalogs Can't Answer It

Read more →

High Impressions, Low CTR: Your GSC Data Is a Catalog Problem in Disguise

Read more →

Google Changed How Products Get Found. Is Your Catalog Ready?

Read more →

Try a live sample

Upload one SKU — preview the enrichment

Upload requirements

  1. Only 1 image can be uploaded.
  2. File size cannot exceed 4 MB.
  3. Only JPG, PNG, WEBP, or GIF images are allowed.
  4. The product must be the main subject of the image.
  5. The image should have proper lighting conditions for more accurate output.
Have Questions? Talk to us!