Soham360 — AI News Agent
AI-Powered News Aggregation with Automated Analytics Reports
AI that reads the news, surfaces what matters, and delivers actionable analytics reports — automatically.
Who We Built This For
Soham360 is a media intelligence platform built to help organisations, analysts, and decision-makers cut through news overload. Rather than manually scanning dozens of publications, the platform uses AI to aggregate, process, and distil the most relevant news across topics — and delivers structured analytics reports that surface trends, sentiment shifts, and key developments without any manual effort.
What We Set Out to Build
Soham360 was designed to solve a problem every organisation faces: there is more news published every day than any team can realistically monitor. Keeping track of industry developments, competitor activity, regulatory changes, and market signals across multiple sources requires constant attention that most teams simply cannot sustain.
The AI News Agent at the core of Soham360 automates the entire monitoring-to-reporting pipeline. It continuously pulls news from dozens of curated sources across categories, processes each article through an AI layer that extracts key entities, sentiment, relevance scores, and topic clusters — and builds a structured knowledge base that updates in real time.
The analytics reporting engine takes this enriched data and automatically generates structured reports — daily digests, weekly summaries, topic-specific deep dives — and delivers them to subscribers on a configurable schedule. Reports include trend analysis, sentiment tracking over time, source comparison, and flagged high-importance items requiring attention.
The result is a platform that replaces hours of daily news scanning with a concise, AI-generated intelligence briefing — delivered automatically, with the depth and context needed to act on it.
Project Facts
Tech Stack
What Needed to Be Solved
Keeping track of relevant news across multiple sources, categories, and geographies is an overwhelming manual task. Important developments get missed, analysis is delayed, and the cost of employing people purely to monitor and summarise news is prohibitive for most organisations. A fully automated, AI-driven pipeline was needed.
News volume across dozens of relevant sources exceeded what any team could monitor manually without missing critical developments
Manual summarisation of articles was slow, inconsistent in quality, and consumed significant analyst time that could be spent on higher-value work
No unified view existed to spot trends, sentiment shifts, or topic momentum emerging across multiple publications simultaneously
Periodic reporting required analysts to compile insights manually — a time-intensive process that often delayed delivery of actionable intelligence
Important stories from niche or regional publications were systematically missed because there was no scalable way to monitor them consistently
Subscribers had no ability to customise the topics or categories they monitored — every user received the same undifferentiated news feed
Inside the Platform
Every module is purpose-built to replace a standalone tool — unified in one workspace.
- Real-time articles from dozens of curated sources
- AI-generated summaries for every article
- Relevance scoring and category tagging
- Sentiment indicator per article (positive / neutral / negative)
- Bookmark and save articles for later reference
- Topic trend charts over configurable time ranges
- Sentiment trend analysis per topic or source
- Top entities (people, companies, locations) by mention frequency
- Source comparison — who is covering what
- Breaking story alerts for high-velocity topics
- Daily digest report auto-generated every morning
- Weekly intelligence summary with trend highlights
- Topic-specific deep-dive reports on demand
- Configurable delivery schedule per subscriber
- PDF and email delivery with structured formatting
- Custom topic watchlists per user or team
- Keyword and entity-based monitoring rules
- Real-time alerts for breaking developments
- Source inclusion/exclusion per monitored topic
- Historical topic archive with full search
Everything in One Workspace
AI Article Processing
Every ingested article is processed through an AI pipeline that generates a concise summary, extracts key entities, assigns a sentiment score, and maps it to relevant topic clusters.
Multi-Source Aggregation
Continuously pulls news from dozens of curated RSS feeds, news APIs, and web sources — across national, regional, and niche publications — with deduplication and source quality scoring.
Analytics Reports Engine
Automated report generation on configurable schedules — daily digests, weekly summaries, topic deep-dives — with trend analysis, sentiment tracking, and flagged high-importance items.
Trend & Sentiment Tracking
Tracks topic momentum and sentiment shifts over time, surfacing emerging trends before they become mainstream and flagging sudden sentiment reversals across monitored areas.
Real-Time Alerts
Configurable breaking-news alerts notify subscribers the moment a monitored keyword, entity, or topic spikes in coverage volume — ensuring nothing important is missed.
Custom Topic Watchlists
Each subscriber defines their own watchlists — specific topics, companies, people, or geographic regions — and receives a personalised news feed and reports tailored to their interests.
Searchable News Archive
Full historical archive of all processed articles, searchable by keyword, topic, date range, source, or sentiment — enabling deep research across months of news data.
Scheduled Report Delivery
Reports are automatically formatted and delivered via email or accessible via the dashboard on a user-configured schedule — daily, weekly, or triggered by event thresholds.
How We Built It
Source Onboarding & Configuration
Identified and onboarded relevant news sources across categories, configured RSS feeds and news API integrations, and established source quality and reliability scoring.
AI Processing Pipeline
Built the article processing pipeline — ingestion, deduplication, AI summarisation, entity extraction, sentiment scoring, and topic classification — running continuously in the background.
Analytics Engine
Developed the analytics layer tracking topic velocity, sentiment trends over time, entity mention frequency, and source comparison metrics — powering all dashboard visualisations.
Report Generation System
Built the automated report compiler that aggregates enriched data into structured daily and weekly reports, with configurable templates for different report types and subscriber preferences.
Alerts & Delivery
Implemented real-time alerting for breaking topic spikes, configured email delivery infrastructure, and built subscriber preference management for topics, schedule, and report format.
Full Scope of Work
Built a continuously running news aggregation pipeline pulling from dozens of curated sources across categories with automatic deduplication
Implemented AI article processing using OpenAI to generate concise summaries, extract named entities, assign sentiment scores, and map articles to topic clusters
Developed a trend analytics engine tracking topic velocity, sentiment shifts, and entity mention frequency over configurable time windows
Built an automated report generation system producing structured daily digests and weekly intelligence summaries on configurable schedules
Created a real-time alerting system notifying subscribers when monitored topics spike above configured volume or sentiment thresholds
Designed custom topic watchlist management allowing each subscriber to personalise their news feed and reports independently
Built a full-text searchable historical archive of all processed articles with multi-faceted filtering by source, date, topic, and sentiment
Deployed on AWS with scalable ingestion queues to handle high-volume news days without processing delays
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