For App Builders
You're building a grocery price-comparison app, a meal-planning assistant, or an AI agent that answers "where is this cheapest near me?" The hard part isn't your app — it's the data: thousands of SKUs, dozens of retailers, prices that change daily, and scrapers that break every time a site updates. We run that layer for you. One REST API, matched products across retailers, refreshed on your schedule.
{
"product_id": "8901063092730",
"name": "Britannia Whole Wheat Bread 400g",
"brand": "Britannia",
"retailer": "blinkit",
"zone": "380015",
"price": 45.0,
"mrp": 50.0,
"promo": {"active": true, "type": "discount", "label": "10% off"},
"in_stock": true,
"unit_price": {"value": 11.25, "per": "100g"},
"currency": "INR",
"collected_at": "2026-07-14T08:30:00+05:30"
}Use cases
Matched across retailers by barcode/UPC and pack size — so "1L Coca-Cola" on one store equals "Coca-Cola 1 Litre" on another. Price, promo price, unit price, availability and store/ZIP-level granularity.
Turn a recipe into a live, priced shopping list. Product name, brand, pack size, price, availability by ZIP/postcode — plus nutrition and allergen fields for diet-aware planning.
Stable versioned JSON schemas, documented fields and webhooks that AI agents can query directly. Building on Claude, GPT or Gemini? Data arrives structured, with provenance fields (source, timestamp) your agent can cite.
Restaurant menus, dish-level pricing, ratings and delivery fees from 200+ platforms — for apps built around dishes, not just restaurants.
Coverage
| market | retailers we cover (examples) |
|---|---|
| 🇺🇸 United States | Walmart, Kroger, Albertsons, Target, Publix, Aldi, Costco, Instacart |
| 🇬🇧 United Kingdom | Tesco, Asda, Sainsbury's, Morrisons, Aldi, Lidl, Ocado, Waitrose |
| 🇦🇺 Australia | Coles, Woolworths, Aldi, IGA, Dan Murphy's |
| 🇮🇳 India | Blinkit, Zepto, Swiggy Instamart, BigBasket, Flipkart Minutes, DMart, JioMart |
| 🇦🇪🇸🇦 Gulf | Carrefour, Talabat Mart, Noon Minutes, Nana, HungerStation |
| More | Canada, South Africa, Singapore, Malaysia + 40 markets on request |
Delivery options: REST API · webhooks on price change · scheduled CSV/JSON feeds · direct to S3, BigQuery, Snowflake.
For builders
Most data vendors are built for enterprise procurement. We kept a lane for builders:
Launch path
Markets, retailers, fields, refresh rate.
Validate schema and matching quality against your app's needs.
A small live feed powering your MVP/beta.
Add retailers, markets and refresh frequency as you grow; pricing scales with volume.
Questions
Primarily by barcode/UPC plus pack-size normalization; where barcodes aren't exposed, we use brand + normalized title + size matching with a QA layer. Match confidence is included per record so your app can decide what to display.
Configurable per retailer: from hourly (quick-commerce and volatile categories) to daily or weekly. Webhooks can push only changed prices so you're not re-ingesting full catalogs.
Yes, where retailers publish location-based pricing. US/UK/AU grocery is typically ZIP/postcode-level; Indian quick-commerce is pin-code level. Coverage depth per retailer is confirmed during scoping.
We collect only publicly displayed prices — no logins or member-only data — under GDPR/CCPA-aligned processes, with DPAs available. Many commercial apps and enterprise brands run on this data after legal review.
The pilot is free. Ongoing feeds are scoped by retailers, SKU volume and refresh — small single-market feeds start much lower than enterprise pipelines.
Yes — standard REST with token auth, stable schemas and documented fields that AI agents can query and cite.
Tell us your markets and retailers. Free 1,000-record pilot, no credit card, sample in 48 hours.
Tell us your platforms, markets and fields, and we will deliver a free DoorDash Restaurant sample so you can validate quality ahead of any commitment.
Tell us your platforms, target markets and required fields — we'll map exactly what's possible with food data scraping, recommend the right approach, and send a working sample so you can verify quality before any commitment.
Thanks — our data team will reach out within 48 hours with your sample.
