Scanned product
Oat Bar — Choc Chip
$3.20$2.13 / 100g
BUY
- Good current price for this shelf
- Comparable options are weaker value
- AI audit checked product evidence
Private beta for smarter shopping
Buy, Wait
or Hop.
HOPPD answers the question shoppers actually have in the aisle by combining price, product data and ingredient evidence: should I buy this, wait for a better time, or hop to a smarter alternative?
- 14k+
- product signals in the current test pipeline
- 3
- plain decisions: BUY, WAIT, HOP
- AI-audited
- product and ingredient evidence checked for weird matches
9:41●●● ))) ▭
Woolworths Castle Hill
WAITLikely better sale later
HOPHealth + value alternative
CartYou
BUY Good enough to grab
HOP Better option found
When this is the right pick.
Price, value, product fit and evidence are strong enough. No drama. Put it in the trolley.
When timing matters.
HOPPD watches price history and sale signals so “wait” means more than wishful thinking.
When there is a better move.
Hop to a healthier, better-value, or both-health-and-value alternative that actually matches the same use.
Australian shelf context
Built around stores shoppers already know.
HOPPD’s private-beta data story starts with familiar Australian shelves: supermarket products from Coles and Woolworths, with pharmacy and personal-care lanes for Priceline and Chemist Warehouse.
Coverage varies by category during beta, but the point is simple: scan real products from places people already shop.
How it works
One scan. A real answer. Evidence underneath.
HOPPD is deliberately not a giant comparison table. The first job is to make the immediate shelf decision clear.
Scan the product
Start with barcode identity. If the catalogue needs help, HOPPD can fall back to product/front label or ingredient evidence.
Audit price, ingredients and fit
The engine looks at current price, unit value, sale context, availability, category-specific health signals, ingredient evidence and same-use matching.
Show BUY, WAIT or HOP
The result is one clear recommendation with the reasons, confidence and freshness visible underneath.
AI-audited evidence
Not random product swaps. Audited product signals.
HOPPD reviews product identity, ingredient lists, claims, pricing, unit value and category fit before making a shelf call. AI is the review layer that catches weak evidence, weird matches and suspicious recommendations before they look trustworthy.
Ingredient audit
Ingredients, actives, claims and concern flags are checked against the category instead of being treated as decoration.
Product audit
Barcode identity, retailer source, price, unit value and availability have to line up before the answer is useful.
AI review layer
AI helps flag odd matches and weak explanations. It does not replace deterministic price math or same-use rules.
Why it needs to exist
Supermarket apps tell you what exists. HOPPD tells you what to do.
Normal comparison tools make shoppers do the hard part. HOPPD collapses price, unit value, health evidence, availability and retailer context into a simple decision card.
Same-store first
If you are standing in one store, the main hop should be useful in that store. Cross-retailer wins belong in a separate “elsewhere” lane.
Health + value lanes
A Health Hop can cost more. A Value Hop must actually improve unit value. The best result is both.
AI audit, not AI guessing
AI checks product and ingredient evidence for weirdness. The recommendation still has to survive deterministic price, unit-value and same-use rules.
No-hop is still useful
Sometimes the product in your hand is already a keeper. HOPPD should reward that instead of pretending every scan needs a swap.
iOS-first
Built around the camera, not a spreadsheet.
The app opens like a shopper tool should: camera-first, fast scan modes, then a separate result screen with the three decisions front and centre.
- Barcode exact match first
- Product and ingredient fallback only when useful
- Decision first, evidence second
- Private beta polishing before wider release
Ready to stop guessing at the shelf?
HOPPD is being polished in private beta now. The public site is live; the app rollout comes next.
Request early access