AI analysis of news feeds from newspapers (vernacular and English)

AI analysis of news feeds from newspapers (vernacular and English)

Objective

The aim is to develop a minimal viable product (MVP) that automatically produces a comprehensive, police-relevant daily news digest based on a given date. This digest consolidates and organizes news articles in English, focusing on content that is relevant to specific police districts as defined by senior officers. The system uses AI to filter, group, and cross-reference news topics, providing comparative insights on how different news sources report the same events, and enriching the content with related articles from the previous seven days. The digest is delivered through a simple, user-friendly dashboard or as a PDF report, enabling officers to stay informed efficiently and make well-grounded decisions.

Scope

The solution covers a daily batch process that accepts date-based input from a news API, exclusively handling English-language articles. It leverages GenAI components to filter articles for district relevance, cluster them into coherent topics, and generate comparative summaries aligned with senior officers’ guidelines. Additionally, it attaches historical context by linking the top related articles from the prior week for each topic. The assembled digest is rendered in  PDF format for easy consumption. The MVP excludes real-time news alerts, multilingual capabilities, user authentication, extended archival searches, and mobile app interfaces to focus on delivering core functionalities within a limited timeframe.