Media Monitoring Hub

Structured synthesis, not more noise

Media Monitoring Hub is a lightweight system for ingesting external sources, classifying content by topic and sentiment, and generating structured summaries for communications workflows.

It is built for teams where manual monitoring is slow, inconsistent, and cognitively expensive — where the bottleneck is not access to information, but synthesis.

Designed to reduce daily monitoring time from hours to minutes while preserving editorial oversight.

This is an operational prototype exploring how LLMs can support structured media intelligence. Not replace editorial judgment.

Ingest

Predefined source feeds, normalised and cleaned

Classify

Topic tagging and structured sentiment analysis

Summarise

Concise, formatted coverage digests

Output

Briefing-ready reports in minutes

Monitoring is a filtering tax on attention

Communications teams routinely perform the same costly loop: scan sources, judge relevance, classify by theme, assess tone, and assemble briefings. Every day.

Track dozens of news sources and feeds
Manually scan for relevance across volumes
Categorise stories by theme and priority
Assess tone and sentiment consistently
Prepare internal briefings under time pressure

The bottleneck is not access to information. It is synthesis.

End-to-end monitoring pipeline

Source Ingestion

Pulls from predefined media sources and RSS feeds on a configurable schedule.

Content Extraction

Strips markup, normalises structure, and extracts clean article text.

Topic Classification

LLM-based tagging against a defined taxonomy. Repeatable, auditable prompts.

Sentiment Analysis

Structured sentiment scoring — not vibes. Explicit positive, negative, neutral with rationale.

Summary Generation

Concise, formatted summaries following a defined output schema. No hallucinated flourish.

Briefing Output

Digest assembled and formatted for review. Minutes to read, not hours to compile.

Constrained by design

// system architecture

sources ────→ ingestion layer
              │
              ▼
      content extraction
              │
              ▼
   classification ──→ topic tags
              │
              ▼
    sentiment ──────→ scored output
              │
              ▼
     briefing ──────→ structured digest

// not an autonomous agent.
// a constrained, workflow-aligned assistant.

Deterministic formatting

Outputs follow explicit schemas. No creative interpretation of structure.

Repeatable prompts

Classification prompts are modular and auditable. Same input, same shape.

Explicit output schemas

Every output field is defined. Outputs are schema-bound and confidence-scored to make failure states explicit rather than implicit.

Minimal hidden reasoning

Model behaviour is inspectable. No black-box decisions on classification or tone.

Augment, don't replace

Editorial judgment stays human. The system compresses, not decides.

Where it fits

newspaper

Daily Press Digests

Automated morning briefings from overnight coverage

bolt

Rapid-Response

Real-time monitoring during breaking news or crises

campaign

Campaign Tracking

Message pull-through and narrative analysis across outlets

summarize

Executive Briefings

Structured summaries for leadership review

query_stats

Narrative Analysis

Track how key themes evolve across sources over time