customer_support · ecommerce · workflow
Swiggy builds generative AI neural search, conversational bots, and LLM-powered restaurant partner self-service
Users find it daunting to choose from the many food options on Swiggy's app, unfamiliar dish names create confusion, and restaurant partners lack efficient self-service for onboarding and operational questions.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · User submits open-ended query
Users search using conversational and open-ended queries without needing specific keywords.
Tools used
LLMGPT-4
Outcome
Neural search enables conversational food and grocery discovery, a GPT-4 chatbot handles customer service empathetically, and in-house LLMs power restaurant partner self-service leading to faster issue resolution.
Results
Volume50 million-plus items
Grounding & classification
Source type: technical build writeup
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chatbotcontent generationconversational aiknowledge searchrecommendation systemknowledge baseproduct catalognamed customersource backedtools describedworkflow describedecommercehospitalitycustomer satisfactionresolution time reductiontechnical build writeupcustomer supportecommerce opsautonomous resolutionrag answering