attribute dimensions
in the extraction taxonomy, applied by category
GEO copy fields
written for every product
answer engines
Perplexity anchored, GPT-4o, Gemini
schema.org export
copy-ready in one click
The shift
Shoppers stopped browsing. They started asking. And the AI doing the answering has never read your product page.
Assistants like ChatGPT and Perplexity recommend from structured facts, not marketing prose. A photo and a two-line description tell them almost nothing, so your best pieces never make the shortlist. Being unsearchable is the new being out of stock.
From a single photo to a product AI can actually read.
Upload a photo
Drop in one product image or a whole catalog by CSV. Discovery starts reading the moment the file lands, no attribute forms to fill in by hand.
AI reads it into deep structured data
Category, colour, material, pattern and fit, every attribute extracted with its own confidence score. Anything the model is unsure of gets flagged for a two-second human glance, and your correction trains the next run.
Publish GEO-ready copy, then watch your visibility move
Push approved copy and schema.org JSON-LD back to the store this product came from, then measure whether the assistants start putting you in the answer.
Not a keyword or two. The whole vocabulary of the garment.
Most feeds give an assistant a title and a colour. Discovery gives it the language shoppers actually use to ask.
The extraction goes six taxonomies deep
Occasion, style, season, mood, trend and the exact phrases shoppers type, reasoned from the image rather than copied off the label.
schema.org, ready to paste
Product and FAQ JSON-LD, generated and copy-ready.
You approve what ships
Low-confidence fields are flagged. Correct or approve in seconds.
GEO visibility tracking
Don't just enrich. Prove it.
Enrichment is a bet until you can see it pay off. Discovery asks the answer engines the questions your shoppers ask, records who gets mentioned, and shows your visibility before and after every enrichment, engine by engine.
best black wool coat for winter
Based on what retailers publish, these black wool coats stand out this winter:
- 1.Bexley Row double-breasted overcoat
- 2.Copeland & Marsh cashmere-blend coat
- 3.Fen & Field boiled-wool greatcoat
- 4.Arloway funnel-neck wool coat
- Anima Atelier Wool Coatnot surfaced
Illustrative demo with a sample brand. Scheduled API answers are a proxy for consumer AI surfaces; placement is never guaranteed.
- Perplexity native, GPT-4o and Gemini via web retrieval
- Before and after windows around every enrichment event
- Aggregate comparisons, never a causal promise
It starts from data you already made.
The hardest part of enrichment is a clean starting point. If you make tech packs, you already have one, so Discovery reasons from your own specs instead of guessing.
Source
Your tech-pack data is already structured
- Tech packs and BOM
- Existing product catalog
- CSV or image upload
Discovery
Read, enrich and score
- Deep attribute extraction
- GEO copy and JSON-LD
- Visibility tracking
Publish
Back to the storefront
- WooCommerce
- WordPress
- More stores coming
Start free. Grow into visibility.
Enrich your first products at no cost. Move up when you want every assistant watching your whole catalog.
Free
Enrich your first products and see the depth for yourself.
- Up to 25 products
- Full attribute extraction
- JSON-LD export
- One AI engine tracked
Pro
For a growing catalog that needs to be found across every assistant.
- Up to 2,000 products
- All three answer engines tracked
- Weekly visibility reports
- Bulk import and review queue
Scale
For full catalogs, tech-pack pipelines and multi-store publishing.
- Unlimited products
- TechPack and Woo integrations
- Daily tracking and alerts
- Priority enrichment queue
Be in the answer.
Enrich your first products free and watch them become legible to the assistants your shoppers already trust.