What challenges did Moglix face before AI implementation?

Answer customer product questions at scale and improve product search and selection. Extract structured product data from PDFs for supplier and catalog workflows. Improve sourcing and operational efficiency across industrial ecommerce workflows.

What was the impact of the AI solution?

500+ orders generated over three months. 4% rise in SEO traffic from automated descriptions. 15% improvement in conversion rate. 50% improvement in operational efficiency from OCR-based extraction. Reports and analyses up to 50x faster with BigQuery.

Source

GCPScaled productionEvidence: Medium65/100

Moglix Case Study | Google Cloud

Use case typeProduct discoveryUpdated Jun 13, 2026

Moglix rendered digital transformation and innovation for its clients with Google Cloud's Vertex AI, enhancing product searches, descriptions, data access, and efficiency to improve customer experiences. The company uses Vertex AI for unified natural-language search, automated product descriptions, chatbot responses, corporate information discovery, and OCR-based extraction from PDFs.

Organization: Moglix
Industry: Retail
Location: India
Published: June 2026

Reported outcomes

+50%

productivityProductivity & throughput

4%quantified impact+15%quantified impact50xtime

Strategic outcomes

Customer experience & trustImproved product search and discoveryNew product / capabilityDeployed ecommerce chatbot supportScale & capacityAutomated PDF data extraction workflowsBetter decisions & insightAccelerated reporting and analysis

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

Quantified impact: 4%

Google Cloud Customer StoriesJun 3, 2026Customer storyInferred claimMedium evidence strength

4% rise in SEO traffic from automated descriptions.

Normalized claim

Quantified impact: 15% increase

Google Cloud Customer StoriesJun 3, 2026Customer storyInferred claimMedium evidence strength

15% improvement in conversion rate.

Normalized claim

Productivity: 50% increase

Google Cloud Customer StoriesJun 3, 2026Customer storyInferred claimMedium evidence strength

50% improvement in operational efficiency from OCR-based extraction.

Normalized claim

Time: 50 x increase

Google Cloud Customer StoriesJun 3, 2026Customer storyInferred claimMedium evidence strength

Reports and analyses up to 50x faster with BigQuery.

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: Moglix
Provider: GCP
Maturity: Scaled Production
Linked source: Google Cloud Customer Stories

Answer customer product questions at scale and improve product search and selection

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 3 of 4

1Ecommerce search and discovery
2Customer support automation
3Document OCR and extraction

Answer customer product questions at scale and improve product search and selection.
Extract structured product data from PDFs for supplier and catalog workflows.
Improve sourcing and operational efficiency across industrial ecommerce workflows.

Deployed a Vertex AI-powered ecommerce chatbot to answer customer queries and support product discovery.
Used Vertex AI to enable unified natural-language search and automated product descriptions.
Applied generative AI for vendor discovery and OCR-based data extraction from PDFs.
Used BigQuery as a data lake to speed reporting and analysis.

Technologies

Vertex AI BigQuery Google Cloud