Swiggy rolls out AI assistant Guru for 2.7 lakh restaurant partners

Guru is now available to restaurant partners across more than 720 cities, offering insights on payouts, campaigns and menu performance. Swiggy also reported a narrower Q1 net loss as it pursues a ₹10,000 crore adjusted EBITDA target by FY31.

— Source published Mon, 17 Aug, 2026, 16:41 IST · First seen Mon, 17 Aug, 2026, 16:51 IST · Source CNBC-TV18 · Companies

What happened

Swiggy launched Guru, an AI assistant for 2.7 lakh restaurant partners across 720+ cities, offering payout, campaign and menu-performance insights. The company

Key facts

  • Guru rolled out across over 720 cities
  • Accessible to 2.7 lakh restaurants
  • Q1 consolidated net loss: ₹791 crore vs ₹1,197 crore year earlier
  • Revenue from operations: ₹6,812 crore, up 37.3% YoY
  • EBITDA loss: ₹650 crore vs ₹945 crore
  • Overall revenue: ₹7,112 crore, up 34% YoY
  • Food delivery GOV: ₹9,490 crore, up 17.4% YoY
  • FY31 adjusted EBITDA target: ₹10,000 crore
  • FY31 consolidated GOV target: around ₹2.5 lakh crore vs ₹67,734 crore in FY26
  • Expected consolidated GOV CAGR: over 30% for five years

Why this matters

The broad deployment positions Swiggy as a deeper operating-system partner to restaurants, making adjacent opportunities in merchant SaaS, advertising, payments and supply-chain services more strategically relevant.

What to watch

  • Guru monthly active restaurant partners, repeat usage and action-conversion rates.
  • Changes in restaurant churn, exclusive/priority partnerships and order-share migration between Swiggy and Zomato.
  • Growth in ad revenue, partner-funded discounts and campaign participation after rollout.
  • Restaurant complaints related to payout accuracy, recommendation bias, commissions or promotional ROI.
  • Evidence that Guru lowers support-ticket volume and partner servicing cost per order.
  • Competitor launches of AI merchant copilots or expanded restaurant analytics tools.
  • Swiggy's quarterly adjusted EBITDA trajectory versus its FY31 ₹10,000 crore target.
  • Connect Guru recommendations to one-click actions for ads, discounts, menu edits, inventory availability and operating hours.
  • Use aggregated partner data to identify cuisine, locality and daypart supply gaps, then target restaurant acquisition and cloud-kitchen partnerships.
  • Bundle Guru with higher-margin merchant services such as sponsored listings, analytics subscriptions, packaging, financing or POS integrations.
  • Measure whether AI-led recommendations increase partner-funded promotions faster than they improve restaurant contribution margins.
  • Deploy human escalation and transparent payout/campaign explanations to prevent the tool from being viewed as a commission-optimization mechanism.