Flagship product
National Information Resilience Enhancement System
An AI-powered narrative intelligence platform that monitors thousands of news outlets and social media channels in real time, detects issue signals before they become crises, and turns big data into strategic insight for leadership.
Workflow
NIRES unifies the entire public-information workflow, from signal filtering to impact measurement, in a single cycle that keeps learning.
Preparing clean, relevant data.
Turning data into structured narrative understanding.
Converting insight into recommendations and follow-up.
Measuring action effectiveness for continuous improvement.
Modules
Each module handles one specific stage of the workflow, and its output feeds the next.
Cluster 01
Module
Daily media monitoring produces huge volumes of data, most of it irrelevant noise. Without effective filtering, analysts spend their time sorting data instead of analyzing it.
The first gate that automatically filters incoming data and separates relevant content, so attention goes to the issues that truly matter.
Module
Not all relevant content contains an event; much of it is opinion or reaction. Telling event-driven narratives apart from opinion is key to weighting an issue and judging its urgency.
Analyzes narratives to detect whether an event is present, separating descriptive content from event-driven narratives and reading the data through the Signal–Mechanism–Context (SMC) framework.
Cluster 02
Module
The bridge between narrative data and AI processing. It translates information needs into instructions the AI workflow understands, and completes the SMC mapping with the Mechanism and Context dimensions.
Module
Interprets how the data should be read, based on the settings in the Strategic Context Orchestrator. That reading produces analysis that stays close to the context you actually need.
Module
Issues are rarely brand new; they are often a repeat, development, or escalation of earlier ones. Without a historical baseline, recommendations risk ignoring established patterns and precedents.
Compares the latest insight against historical data and uses the matches as added context, so recommendations are more precise and grounded in precedent.
Cluster 03
Module
Converts history-enriched insight into concrete, actionable recommendations, weighing the issue’s position in the Matrix, dominant public emotion, main spreading platform, and response urgency.
Module
Without structured task management, recommendations risk never being carried out or overlapping between units.
Turns every recommendation into a structured task ticket that can be selected, authorized, and handed clearly to the responsible unit, at the right time and through the right channel.
Cluster 04
Assesses whether a communication response on social media shifted public perception, calmed escalation, or triggered new reactions, by analyzing how public conversation evolves afterward.
Measures the impact of news publications through reach, shifts in news framing, and changes in the issue’s position on the Matrix, so every step has a clear, measurable outcome.
Features
One unified platform to understand the information landscape: what is being said, who is saying it, where, and where it is heading.
Collects and filters data from online news and social media (X, Instagram, Facebook, TikTok, YouTube) to identify issues and trends early.
AI acts as a data gatekeeper, reads how narratives develop, and flags early signals that may escalate into a crisis.
Conversation trend charts, News Media vs Social Media spike comparison, and positive, neutral, and negative sentiment ratios.
Interactive visualization of how issues spread across Indonesian regions, showing where narratives concentrate and move.
Turns massive data into strategic context and analytical insight to support leadership decisions.
Issue quadrants, narrative flows, and issue prioritization, with measurable response recommendations and transparent AI reasoning.
AI executive summaries, situation reports, and impact evaluation covering reach, engagement, and sentiment shift.
API connectors for external data, customizable visual identity, and light and dark modes.
Issue Matrix
Every issue is mapped by relevancy and virality, so teams can prioritize responses objectively instead of reacting to noise.
Public Noise
Widely discussed but low relevance. Monitor only.
Priority Focus
Relevant and viral. Needs an immediate response.
Minor Signal
Weak and low-relevance signal. Kept as context.
Latent Risk
Relevant but not yet viral. Watch before it grows.
Relevancy
Virality →
AI Recommendation
Based on issue analysis, NIRES recommends the most appropriate communication approach, with traceable reasoning.
Realign
Realign messaging when a narrative drifts away from facts or policy.
Counter
Prepare data-backed counter-narratives against misinformation.
Explain
Provide explanation or clarification on issues causing public confusion.
Engage
Engage audiences directly to build understanding and trust.
Track public perception of policy, detect misinformation early, and prepare the right public communication.
Reputation management, early crisis detection, and measuring corporate communication effectiveness.
Strengthen an organization’s ability to withstand disinformation and fast-moving information dynamics.
NIRES is designed for high-security environments and can run on-premise on your own infrastructure.
NIRES (National Information Resilience Enhancement System) is an AI-powered narrative intelligence platform by Artha Solusi Indonesia that monitors news and social media in real time, detects issues early, and provides strategic response recommendations.
NIRES monitors thousands of online news outlets and five major social media platforms: X, Instagram, Facebook, TikTok, and YouTube. Other external data can be connected through API connectors.
NIRES uses Large Language Models (LLMs) to filter and cluster issues, detect narrative developments, suggest keywords and indicators, explain the reasoning behind response recommendations, and compose executive summaries.
SMC is the NIRES framework for reading how a narrative is built: Signal (the emerging signal or event), Mechanism (how the narrative spreads and develops), and Context (the background that gives it meaning). Narrative Event Detection maps the signal, and the Strategic Context Orchestrator completes the Mechanism and Context dimensions.
The Issue Matrix maps every issue by relevancy and virality into four quadrants: Priority Focus, Latent Risk, Public Noise, and Minor Signal. An issue’s position in the Matrix is one of the inputs for response recommendations and impact measurement.
Yes. NIRES can run on-premise on your organization’s infrastructure, including GPU servers for AI processing, so your data stays under your control.
Contact our team via the contact page or email. We will schedule a demo session and a requirements discussion.
Schedule a demo and discuss your organization’s information intelligence needs with our team.