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SwiggyIntegration

Swiggy adopts Snowflake as unified data foundation to accelerate insights

What happened

Swiggy is leveraging Snowflake's platform as a unified data foundation to support its marketing, operations, and business execution.

Source

Article excerpt

Highlighted: the sentence this signal was extracted from

Snowflake has announced that Swiggy is leveraging its platform as a unified data foundation to support marketing, operations and business execution across its food delivery, Instamart and Dineout businesses. As Swiggy scaled to serve millions of customers across its businesses, fragmented data created challenges in accessing insights. The company sought a unified serving layer capable of supporting peak workloads, while also enabling teams to access insights through self-service tools and reducing dependency on central data teams. Swiggy has established a central analytical layer on Snowflake using Apache Iceberg. According to Snowflake, this has improved the company's slowest data workflows by 90% to 96%. The company has also reduced the processing time for its heaviest queries from two hours to 15 minutes, while data processing has moved from six hours to near real time. The improvements are being used across functions. Marketing teams can build and launch targeted campaigns directly within their own tools, while product engineering teams use standardised metric definitions to assess experimental features before release through an in-house platform running on Snowflake. Operational teams are using real-time service quality metrics to monitor and proactively improve delivery logistics. Finance teams, meanwhile, have gained workload-level visibility into technology expenses...

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Extracted by Autobound

From the Signal API record
Event
Integration

What this signalsA new integration often shows which tools the company builds around.

Product
Snowflake
Location
India

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The full record

From the Signal API record

Topics and mentions

Product tags

  • data
  • general technology
  • online technology

Extraction

Confidence
95%
Detected
Sep 10, 2026
signal_type
news
signal_subtype
integrates_with

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The API returns more than this page shows

This page shows a preview. The full news record in the Signal API and MCP can also have these 8 fields. Some fields are empty for some signals.

Company

  • linkedin_urlValue in the API
  • industriesValue in the API
  • employee_count_lowValue in the API
  • employee_count_highValue in the API
  • revenueValue in the API
  • descriptionValue in the API

Signal

  • signal_nameValue in the API
  • associationValue in the API
Show the full JSONThe record on this page and the API request

GET /v1/signals/99fb1cec-8dd7-69a5-f88e-459bdfb23dba returns this record as JSON. POST /v1/companies/enrich returns every signal for swiggy.com.

{
  "signal_id": "99fb1cec-8dd7-69a5-f88e-459bdfb23dba",
  "signal_type": "news",
  "signal_subtype": "integrates_with",
  "detected_at": "2026-09-10T06:02:47+00:00",
  "company": {
    "name": "Swiggy",
    "domain": "swiggy.com"
  },
  "data": {
    "url": "https://www.adgully.com/post/20412/swiggy-adopts-snowflake-as-unified-data-foundation-to-accelerate-insights",
    "title": "Swiggy adopts Snowflake as unified data foundation to accelerate insights - Adgully.com",
    "excerpt": "Snowflake has announced that Swiggy is leveraging its platform as a unified data foundation to support marketing, operations and business execution across its food delivery, Instamart and Dineout businesses. As Swiggy scaled to serve millions of customers across its businesses, fragmented data created challenges in accessing insights. The company sought a unified serving layer capable of supporting peak workloads, while also enabling teams to access insights through self-service tools and reducing dependency on central data teams. Swiggy has established a central analytical layer on Snowflake using Apache Iceberg. According to Snowflake, this has improved the company’s slowest data workflows by 90% to 96%. The company has also reduced the processing time for its heaviest queries from two hours to 15 minutes, while data processing has moved from six hours to near real time. The improvements are being used across functions. Marketing teams can build and launch targeted campaigns directly within their own tools, while product engineering teams use standardised metric definitions to assess experimental features before release through an in-house platform running on Snowflake. Operational teams are using real-time service quality metrics to monitor and proactively improve delivery logistics. Finance teams, meanwhile, have gained workload-level visibility into technology expenses...",
    "product": "Snowflake platform",
    "summary": "Swiggy is leveraging Snowflake's platform as a unified data foundation to support its marketing, operations, and business execution.",
    "location": "India",
    "planning": false,
    "image_url": "https://erp.adgully.com/artical_image/aff95cf111db39d4e6c860ff7a8af156.jpeg",
    "confidence": 0.95,
    "product_data": {
      "name": "Snowflake",
      "full_text": "Snowflake platform",
      "fuzzy_match": false
    },
    "product_tags": [
      "data",
      "general_technology",
      "online_technology"
    ],
    "published_at": "2026-09-10T06:02:47Z",
    "location_data": [
      {
        "region": "Southern Asia",
        "country": "India",
        "continent": "Asia",
        "fuzzy_match": false
      }
    ],
    "article_sentence": "Snowflake has announced that Swiggy is leveraging its platform as a unified data foundation to support marketing, operations and business execution across its food delivery, Instamart and Dineout businesses.",
    "related_company_name": "Snowflake",
    "related_company_domain": "snowflake.com"
  }
}

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