Built an AI-driven news aggregation and recommendation platform that delivers personalized, real-time news updates to users. The system leverages natural language processing (NLP) and machine learning models to curate, categorize, and summarize news from multiple trusted sources.
Key Features:
Automated News Aggregation – AI scrapes and collects news from verified sources in real time.
Smart Categorization – NLP models classify news into topics like politics, finance, sports, and technology.
Personalized Recommendations – Machine learning algorithms analyze user behavior to suggest relevant articles.
AI Summarization – Long articles are condensed into short, readable summaries without losing key context.
Sentiment Analysis – Detects tone (positive, neutral, negative) to provide deeper insights into trending stories.
Multi-Platform Delivery – Accessible via web, mobile, and API integration.
Scalable SaaS Architecture – Cloud-based infrastructure with role-based access for publishers and end-users.
Impact:
The platform improved content discovery and engagement, helping users stay updated with relevant news while reducing information overload. Publishers benefited from higher user retention and actionable analytics.