A Healthy Restaurant Database for India — Diet-Led Restaurants, Cafés and Cloud Kitchens Across Delivery Apps and Map Listings
How Food Data Scrape scoped a healthy restaurant database India-wide for a nutrition-analysis company, using public listing data delivered by API.
Key takeaways
Key takeaways
A Mumbai nutrition-analysis company asked Food Data Scrape for a healthy restaurant database India-wide: restaurants, cafés and cloud kitchens that sell healthy or diet-led food. Our plan merges public delivery-app and map listings, tags each outlet against clear healthy rules, and delivers the dataset through an API feed at public business-listing level.
Client overview
What did the client need?
The client provides detailed nutritional analysis. It wanted one list of healthy-food brands across India – restaurants, cafés and cloud kitchens – mapped to the Health & Specialty Diet category.
The client was open to API integration, so the data had to arrive as a repeatable feed. Owner and point-of-contact details were excluded: the dataset stays at public business-listing level, with no personal contacts.
The challenge
What made this hard?
- No single "healthy" label. Platforms use their own collections and filters, so a common definition had to be built.
- Health claims vary. "Keto", "high protein" and "clean eating" must be mapped to set tags.
- Cloud kitchens are hard to see. Delivery-only brands often lack map listings and may share one kitchen.
- Same brand, many listings. Names and addresses differ across Zomato, Swiggy and Google Maps.
- Nutrition data is patchy. Most menus show few or no calorie details.
Under FSSAI's 2020 labelling rules, only chains with a central licence or outlets in ten or more locations must show calories per serving, so smaller outlets usually do not.
The solution
How did Food Data Scrape solve it?
We built the universe of outlets first, then applied a documented healthy rule set before any delivery.
Approach
- Start from the India outlet base. Pull public listings from our India restaurant database workflow across Zomato, Swiggy and Google Maps.
- Use platform signals. Read public cuisine tags, healthy collections and menu keywords; Swiggy launched a nutritionist-curated Health Hub in 2020.
- Apply healthy tagging rules. Tag an outlet when its cuisine or share of diet-labelled items passes a set threshold (for example, a diet-led cuisine tag, or 30% or more of menu items with healthy or diet labels), using our health and specialty diet taxonomy.
- Match across sources. Merge listings by name, address and coordinates, plus public fields like Google Places vegetarian-food flags.
- Capture public nutrition. Keep calories and macros where menus show them, as in our nutrition and allergen data work.
- Deliver by API, stay compliant. FDS sends the dataset as an API or feed, respecting robots.txt, site terms and rate limits. No Swiggy or Zomato order or POS integration is offered.
Data captured
Data attributes / fields
The table shows fields typically included in this kind of project; the exact field list is agreed with each client during scoping.
| Field | Description |
|---|---|
| brand_id | Stable internal ID for each healthy-food brand |
| outlet_name | Outlet name as shown on the public listing |
| outlet_type | restaurant, café or cloud_kitchen |
| city_locality | City, locality and PIN code from the public listing |
| lat_long | Map coordinates used for cross-source matching |
| source_platforms | Where the outlet is listed: Zomato, Swiggy, Google Maps |
| diet_tags | Tags such as vegan, keto, high_protein, gluten_free, low_calorie |
| healthy_score_reason | Which rule tagged the outlet as healthy |
| menu_nutrition_shown | Calories or macros where the public menu displays them |
| rating_and_count | Public rating and rating count, captured with date |
Client testimonial
In the client's words
“The healthy restaurant database gave us a more consistent way to identify diet-focused restaurants, cafés and cloud kitchens across India. The diet tags, outlet-level records and API delivery made it easier for our team to review restaurant coverage and support nutrition analysis.”
— Product Strategy Lead, Nutrition-Analysis Company
Results
What were the results?
- One pan-India healthy list. A de-duplicated list of healthy restaurants, cafés and cloud kitchens, with one record per outlet across Zomato, Swiggy and map listings.
- Transparent tagging. Each outlet carries its tagging rule, so the client's nutritionists can review and adjust borderline cases.
- Coverage. The scope is pan-India; brand and outlet counts by city are reported in each delivery.
- Feed in place. The list is delivered as an API feed with a CSV export and refreshed monthly.
Questions
Frequently Asked Questions
Written rules based on public cuisine tags, platform collections and diet-labelled menu items. Each outlet keeps its tagging reason.
No. We provide public business-listing data only – outlet name, location, cuisine and ratings – never personal contacts.
Yes. Food Data Scrape can deliver the dataset as an API or scheduled feed. This is not a Swiggy or Zomato order or POS integration.
Yes, where they have public delivery-app listings. Brands sharing one kitchen are linked when public names and addresses match.
Need a healthy restaurant database for India?
Tell us the cities, diet categories and delivery format you need, and we will scope a pan-India feed with monthly refresh. Visit fooddatascrape.com to discuss your data requirement.
