Trust & Transparency
How we earn your trust.
Rigorous methodology, transparent accuracy tracking, and responsible AI use. We believe intelligence you cannot audit is not worth trusting.
Our Principles
Every design decision in ConflictRadar follows these commitments.
Multi-Source Corroboration
Every alert is cross-referenced against multiple independent sources before surfacing. Single-source reports are flagged, not promoted.
Tiered Reliability
Sources are scored on track record, independence, and proximity to events. Higher-tier sources carry more weight in severity scoring.
Calibrated Confidence
We assign probability-weighted confidence to every assessment. Our public forecast record tracks how well those probabilities hold up against reality.
Intelligence Pipeline
From raw signal to actionable alert — every step is designed for accuracy and speed.
Ingest & Normalize
Structured and unstructured data from diverse global sources is continuously ingested, normalized into a common schema, and timestamped.
Classify & Score
Events are classified by type, region, and severity using a combination of rules-based logic and AI-assisted enrichment with human oversight.
Deduplicate & Correlate
Same-event reports from different sources are clustered together. Corroboration across independent channels increases confidence scores.
Verify & Deliver
High-severity events trigger additional verification steps. Once confidence thresholds are met, alerts are delivered through your configured channels.
Responsible AI Use
AI augments our intelligence pipeline under strict guardrails.
Transparent by Default
Every AI-assisted output is labeled. Per Article 50 of the EU AI Act, all AI-generated content in the product carries a disclosure marker.
Human in the Loop
AI augments analyst workflows — it does not replace human judgment on critical assessments. Confidence thresholds prevent unreviewed AI outputs from triggering alerts.
Auditable Accuracy
Our forecast accountability dashboard publicly tracks prediction accuracy. If the model is wrong, it is visible. No black boxes.
Known Limitations
We believe honesty about limitations is a strength, not a weakness.
⚠Coverage is strongest in regions with high open-source reporting density. Some areas have inherent delays.
⚠Machine translation is broad but imperfect — nuance and entity relationships can be affected.
⚠AI confidence thresholds reduce noise, but sub-threshold signals may still warrant analyst attention.
See our accuracy for yourself.
Track our public forecast record — every prediction, every outcome, no hiding.