Extract Swiggy Instamart Data
Instamart assortment, pricing, and availability — cleaned and comparable.
Tell AuraCrawl what you need from Swiggy Instamart in plain language: "match these 1,200 SKUs against Blinkit and Zepto nightly," or "track price and stock for this category in five cities." Because Instamart lives inside the Swiggy app ecosystem, its web data sits behind serious protection. Getting through it reliably is an engineering problem — one we solve for a living.
What a response looks like
REQUEST
ask“Tell AuraCrawl what you need from Swiggy Instamart in plain language — which entities, which fields, how often. That sentence is the spec.”
{
"sku": "si-330582",
"product_name": "Maggi 2-Minute Masala Noodles",
"pack_size": "4 x 70 g",
"category_path": [
"Snacks & Instant Food",
"Noodles & Pasta"
],
"price_inr": 56,
"mrp_inr": 60,
"discount_pct": 7,
"in_stock": true,
"delivery_eta_minutes": 11,
"city": "Mumbai",
"pincode": "400050"
}What you can extract
- SKU names, pack configurations, and categories
- Price, MRP, and effective discount
- Availability by city and serviceable zone
- Delivery-time promises per location
- Cross-platform SKU matching inputs (name, pack, brand)
- Promotion and banner placement data
PIPELINE Aura Strike gets through Instamart's app-ecosystem defenses; Aura Build normalizes pack sizes so cross-platform comparisons are actually comparable.
Request Swiggy Instamart data.
Describe the fields, the volume, and the cadence. We scope the extraction and deliver a sample before you commit.