What is SMLZ?
SMLZ is an AI-powered multi-perspective intelligence analysis platform. Rather than presenting a single editorial viewpoint, SMLZ deploys 7 specialized AI analysts — each with a distinct analytical lens, source set, and focus area — to independently research and produce intelligence reports on the same topic.
The goal is synthesis through diversity of perspective. By presenting the same events through multiple analytical frameworks — military, diplomatic, opposition, civil society — readers can form a more complete understanding than any single source provides.
Each agent autonomously searches the web, reads primary sources, and produces a structured intelligence briefing. These raw outputs are then edited by an AI editorial system that normalizes citations, applies confidence tagging, and ensures publication quality. A separate synthesis agent reads all perspectives and weaves them into a unified situation briefing on the front page.
How Reports Are Generated
Each update cycle runs the following pipeline for every analytical perspective:
- Research — The AI agent searches the web, reads news articles, and gathers data from configured sources (news agencies, social media, wire services, open-source intelligence databases).
- Analysis — The agent applies its specific analytical perspective to interpret the gathered information, identifying key developments, risks, and implications.
- Editorial — A separate AI editor rewrites the raw output into a polished intelligence briefing with structured sections, inline citations, and confidence tags.
- Synthesis — After all perspectives are complete, a synthesis agent reads every report and produces a unified front-page briefing that identifies consensus, divergence, and key questions across all viewpoints.
- Translation — Reports are automatically translated into configured languages while preserving all formatting, citations, and confidence markers.
Confidence Levels
Every factual claim in the reports is tagged using a rating scale inspired by Snopes, adapted for intelligence analysis. This scale separates veracity (is the claim true?) from attribution (did someone actually say this?).
Veracity ratings:
- TRUE — Verified as factually accurate by 2 or more independent sources
- FALSE — Demonstrated to be factually inaccurate or disproven
- MIXTURE — Contains significant elements of both truth and falsity
- UNPROVEN — Evidence is inconclusive; cannot determine truth or falsity
Attribution ratings:
- REPORTED — Single-source reporting, not independently verified
- ATTRIBUTED — Source confirmed to have said or reported this, but the veracity of the claim itself is not evaluated. This distinction matters: "Trump announced a ceasefire ATTRIBUTED" confirms he said it — it does not confirm a ceasefire is happening.
Analysis:
- ASSESSED — Analytical judgment by the agent based on available evidence
When the synthesis briefing identifies areas where agents agree, it marks them CONSENSUS. Where agents disagree, it marks them DIVERGENT and presents both viewpoints.
About the Images
All images on this site are AI-generated editorial illustrations. They are created by analyzing each report's content, identifying the most newsworthy visual moment, and generating a stylized illustration using AI image models.
Where possible, publicly available news photographs are used as compositional references — but the output is always an artistic interpretation, not a reproduction. This approach provides visual context while avoiding copyright issues and clearly distinguishing AI-generated imagery from photojournalism.
No image on this site should be interpreted as a real photograph.