AI News Aggregation & Automation Tools
Automated news ingestion system with similarity detection and duplicate removal using Perplexity API and OpenAI Embeddings.
01Overview
Built to eliminate manual news monitoring, this system automates the ingestion, deduplication, and reporting of industry-specific news. It ensures stakeholders only see high-signal, unique content.
02Features
- Real-time topic-based automated news ingestion
- Embedding-based similarity detection for duplicate removal
- Content clustering for high-level industry trends
- Multi-user isolation and structured reporting workflows
- Cost-optimized caching layer for expensive API calls
03Engineering Decisions
Selected OpenAI Embeddings to perform semantic deduplication, which is far more accurate than simple string matching.
Designed a robust caching layer to reduce API costs while maintaining real-time freshness.
Built a modular ingestion pipeline that can be easily extended to new news sources.
04Challenges & Solutions
Challenge
Duplicate news coverage across multiple sources.
Solution
Calculated vector embeddings for article content and used cosine similarity to automatically flag and group duplicates.