AI Product Catalog& Asset Library For JM Enterprise
This AI product catalog and asset library gives e-commerce and retail teams one web app for product data and media. Auto-tagging, background removal and omnichannel sync replace old files and folders.
Client Requirement
The client needed a scalable, cloud-native web application to keep thousands of product SKUs and high-resolution media in one place. It had to tag images with AI, find files fast with semantic search and keep access safe by role.
The platform also had to end manual data entry, cut time-to-market for new collections, sync data across all channels live and connect with the e-commerce platforms already in use.
The Solution
We built an AI-driven enterprise web application on a centralized PIM-DAM architecture with modern microservices. Computer vision tags media, cleans backgrounds and matches SKUs on its own, so no one needs to review files by hand.
A GraphQL API moves data between services, while elastic cloud infrastructure handles bulk asset changes, so merchandising teams publish clean catalogs to every channel in seconds.
Our Development Process
Study Catalog Needs:
Design Central Hub:
Build Vision Pipelines:
Add Search And Sync:
Test And Launch:
Visual Showcase
Key Features
Auto Tagging:
Computer vision spots product traits, colors and media types as soon as a file uploads, so manual tagging is gone and metadata indexing speed jumped by 75% across millions of SKUs.
Smarter Search:
Vector-based semantic search lets teams find media using plain language, not exact filenames, so even vague search terms surface the right assets and query accuracy went up by 60%.
Background Removal:
Deep-learning models remove backgrounds and standardize canvases as images upload, so merchandisers get web-ready photos fast and asset creation costs fell by 50% for new launches.
Channel Sync:
Automated connectors send product data and updated assets right to storefronts, marketplaces and ERP systems, so listings stay in sync and multi-channel update latency fell by 85%.
Technology We Used
- Frontend UI/UX
Next.js
React.js
- Backend Framework
Node.js
Python
- Database and Caching
Postgresql
Redis
Frequently Asked Questions
Explore answers to the most common questions about our services, workflows, and support. Clear information, all in one place.
What is an AI product catalog and asset library?
It is a web application that combines Product Information Management and Digital Asset Management into one workspace, using AI to automate media tagging, metadata extraction, background removal and multi-channel publishing for e-commerce teams.
What is the difference between PIM and DAM software?
DAM organizes and distributes digital files like images and videos, while PIM manages structured product information like descriptions and specifications for multiple sales channels. This platform combines both, so teams work from one catalog instead of two separate systems.
How does AI improve digital asset management in web apps?
Computer vision indexes images automatically, applies descriptive tags, strips backgrounds and flags duplicate files, while semantic search lets teams find assets using natural language. Here, that automation increased metadata indexing speed by 75%.
What are the benefits of automated visual tagging for e-commerce catalogs?
Automated tagging removes manual data entry, so thousands of SKUs get accurate, searchable metadata as soon as media uploads. Teams launch new collections faster, and search precision across the catalog improved 60% in this deployment.
How do you sync a product catalog across multiple sales channels in real time?
Automated connectors push enriched product data and optimized media directly to storefronts, marketplaces, and ERP systems as soon as changes happen. This platform cut multi-channel update latency by 85%, so listings stay accurate everywhere at once.
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