Categorizing and risk rating products

Improving product safety and compliance in e-commerce

Hero image


Understanding risk within e-commerce

E-commerce platforms, especially those using third-party sellers like Amazon, Shopify, and eBay, need to make sure their products are safe and meet regulations. Manually reviewing product titles and descriptions to find potential risks is slow and often leads to mistakes.


Efficient Risk Categorization with OmniAI

By leveraging AI language and classification models OmniAI transforms lengthy manual reviews into swift, accurate assessments. In this case study, we’ll do the following:
  • Data collection

    OmniAI connects to the Amazon product listings, pulling titles and descriptions.
  • Risk identification

    Custom AI models are trained to identify and categorize potential risks like choking hazards, fire risks, and battery malfunctions.
  • Data integration

    The identified risks are then cataloged and integrated into the Omni warehouse for easy access and analysis.
  • Rapid onboarding

    The time to onboard new sellers is significantly reduced, from over 48 hours to mere minutes, regardless of the SKU volume.

Define your schema

Here, we’ve defined possible values for the hazard types (FALLING_HAZARD, BATTERY_MALFUNCTION, CHOKING, etc.) along with any additional fields we want to extract.When we run the sync, we’ll have a table that combines our existing data, with the newly extracted columns.
2 description: "Array of possible hazards associated with a product."
3 options:
7 - ...
8 type: "String"
11 description: "Who this product was purchased for"
12 options:
13 - "SELF"
15 - "SPOUSE"
16 - "PARENT"
17 - "FRIEND"
18 type: "String"
Transform data image

Transform your data

The company now has a dynamic database that automatically updates with risk assessments for each product. From here, we can query this table directly with SQL, or ingest it into a variety of BI tools.


From manual review to an automated system

Bringing in OmniAI sped up adding new sellers and also offered great insights into product safety. For instance, an unexpected rise in BATTERY_MALFUNCTION risks in a specific category of products was quickly identified and addressed.Switching from manual checks to an automated AI system, OmniAI has helped our client create a safer and more rule-following e-commerce world. This builds trust and reliability for everyone buying and selling.
[@portabletext/react] Unknown block type "image", specify a component for it in the `components.types` prop

E-Commerce resources

See how OmniAI helps different use cases in e-commerce.

Case study icon

Tagging high-risk products

Analyze product descriptions and reviews to identify and flag potential hazards, ensuring customer safety and compliance.
Case study icon

De-duplicating products

Detect and merge duplicate product listings to maintain a clean, user-friendly shopping experience.
Case study icon

Sentiment analysis in reviews

Extract and analyze customer sentiment from reviews to inform product development and marketing strategies.

Ready to try OmniAI?

Book a demo today and see how our solution can transform your workflow.

Join our Slack to connect with the Omni team and engage with our community.
Set up your environment and connect to our API.
© 2024 OmniAI Technology, Inc.