Ecommerce ops · Production
Nosto Visual AI: ML-powered visual recognition for product recommendations and UGC curation
The problem
(not stated)
Workflow diagram · grounded in source
1
ML visual attribute identification
ai_action
“Visual AI uses advanced machine learning algorithms to automatically identify objects, scenes, events, emotions, styles, colors, patterns, and more within visual content, turning them into machine-readable datasets”
2
Automatic tag application
output
“It then automatically applies tags, enriching the content with metadata, meaning faster content search and quicker publishing”
3
NSFW content detection and disable
validation
“The visual recognition engine can identify inappropriate or offensive content and automatically disable it. This eliminates the tedious task of manual moderation and reduces the potential for human error”
4
Visual recommendations integration
integration
“This visual data is readily available to enhance your product recommendations and personalization strategies based on visual similarities”
Reported outcome
Visual AI eliminates the manual content curation and tagging burden, speeds up content search and publishing, automates NSFW moderation to reduce human error, and enhances product recommendations through visual similarity.
Reported metrics
Content publishing speedfaster content search and quicker publishing
Moderation timesaves you moderation time
Conversionsdriving higher conversions
Human error in moderationreduces the potential for human error
Reported stack
Visual AIHuginn
Source
https://www.nosto.com/commerce-experience-platform/artificial-intelligence/visual-ai
Read source ↗Frequently asked questions
What did this team achieve with this AI workflow?
Visual AI eliminates the manual content curation and tagging burden, speeds up content search and publishing, automates NSFW moderation to reduce human error, and enhances product recommendations through visual simila…
What tools did this team use?
Visual AI, Huginn.
What results were reported?
Content publishing speed: faster content search and quicker publishing; Moderation time: saves you moderation time; Conversions: driving higher conversions; Human error in moderation: reduces the potential for human error (source-reported, not independently verified).
How is this ecommerce ops AI workflow structured?
ML visual attribute identification → Automatic tag application → NSFW content detection and disable → Visual recommendations integration.