AI-Powered Content Tagging & Classification
Tag, categorize, and enrich thousands of articles and assets daily using AI.
Solution Overview
Digital publishers require rich metadata — topic tags, author taxonomy, SEO keywords, content type classification — across millions of articles. Cray deploys NLP models to auto-tag content with 95%+ accuracy, dramatically cutting metadata production costs.
The Manual Process Problem
Editors or dedicated metadata teams manually read each article and assign tags, often taking 15–20 minutes per piece.
Cray's Automation Approach
Fine-tuned NLP classifiers extract entities, topics, sentiment, and SEO keywords from raw content. Tags are suggested with confidence scores. Human review queues handle only low-confidence items.
Key Benefits
Automation Coverage
Target Clients
- Reuters
- Associated Press
- Bloomberg Media
- Condé Nast
- Hearst Communications
Why Cray for Content Tagging?
- 3+ years domain experience
- Deployment in 4–8 weeks
- ROI within 90 days
- 24/7 automated processing
- Enterprise security standards
Related Solutions
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