Normalized claim
Time: 1-2 days
Product approval time fell from 1–2 days to under an hour
Mystore (StoreHippo) uses Gemini on Vertex AI to automate product cataloging and approvals for ONDC ecommerce
Use case typeProduct discoveryUpdated Jun 13, 2026
Mystore, an ONDC ecommerce marketplace, uses Google Cloud AI to boost efficiency and connect millions of buyers and sellers. The platform automates product cataloging and approvals at scale for India’s small and medium-sized sellers, helping them create and maintain accurate listings. Mystore also uses AI for multilingual semantic search, conversational shopping, and support workflows across its seller and buyer experiences.
Reported outcomes
60-70%
productivityProductivity & throughput
1-2 daystime+50%time+20%time
Strategic outcomes
New product / capabilityAutomated product cataloging and approvalsNew product / capabilityImproved product image qualityNew product / capabilityMultilingual semantic product searchScale & capacityScaled to millions of products
Catalog median for productivity & throughput deployments: +40% across 108 reported metrics. Compare benchmarks →
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Productivity: 60-70% increase
Operational efficiency improved by 60–70%
Normalized claim
Time: 50% increase
AI feature deployment became 50% faster
Normalized claim
Time: 20% increase
Response times improved by 20%
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Mystore, StoreHippo
- Provider
- GCP
- Maturity
- Scaled Production
- Linked source
- Google Cloud Customer Story
The platform automates product cataloging and approvals at scale for India’s small and medium-sized sellers, helping them create and maintain accurate listings
Customer identity supportedSource describes one deploymentMaturity supported
Primary read
Use case focus
Showing 3 of 5
- 1Catalog automation
- 2Multilingual semantic search
- 3Conversational AI
- Manual, time-consuming product approval and catalog maintenance for millions of items
- The team needed to improve image quality and speed seller onboarding in a high-volume marketplace
- Buyers needed more effective search and support across regional languages and misspellings
- Integrated Gemini on Vertex AI to automatically generate product titles, descriptions, categories, and HSN codes from product images
- Used Gemini 2.5 Flash Image to improve low-quality product photos by removing backgrounds and centering products
- Applied Vertex AI-based multilingual semantic search to match buyer queries to relevant products even with misspellings or language mismatches
- Built Mystore Genie as a conversational shopping assistant and Mystore Mitra for buyer query resolution
- Used Google Kubernetes Engine to run AI workloads and handle traffic spikes
- Product approval time fell from 1–2 days to under an hour
- Operational efficiency improved by 60–70%
- AI feature deployment became 50% faster
- Response times improved by 20%
- The platform scaled to over 20 million products
Architecture
Mystore integrated Gemini on Vertex AI into its seller dashboard to generate catalog metadata from product images and to improve image quality. It also used Vertex AI for multilingual semantic search, built conversational shopping and support assistants, and ran AI workloads on Google Kubernetes Engine.
Sources & evidence1
Evidence: Medium65/100Evidence strength
- Customer explicitly identified
- Deployment status explicitly supported
- Primary source available
- Quantified outcome available
- Technical implementation details available
Type: Customer StoryPublished: Jun 6, 2026Publisher: Google CloudEvidence: PrimaryConfidence: High
AI-generated summary. Verify important details with the linked sources before relying on this case.
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