Said Horizon continuously ingests multilingual open‑source data—such as local media, NOTAMs, and regional activity logs—to detect weak signals that precede airstrikes, missile launches, drone attacks, and other kinetic threats. Its analytics pipeline correlates anomalies, assigns urgency and confidence scores, and delivers structured JSON alerts via a low‑latency REST API, giving customers hours of early warning before threats appear in mainstream intelligence feeds.
Funding
Funding not disclosed
Founders
Product
Problem
Conventional intelligence sources often miss early, fragmented indicators of imminent kinetic actions such as airstrikes, missile launches, and drone attacks, especially when those signals appear in multilingual open‑source channels. This delay hampers timely threat detection and response for organizations that need to protect assets and personnel.
Solution
Said Horizon continuously ingests multilingual open‑source data—including local media, NOTAMs, airspace restrictions, and regional activity patterns—to surface weak signals that precede kinetic threats. Its analytics pipeline correlates anomalies across sources, assigns urgency, confidence, and source‑strength scores, and generates structured JSON alerts via a REST API. By delivering these early‑warning alerts hours before they appear in mainstream intelligence feeds, customers can prioritize and act on emerging threats more quickly. The service is designed for automated integration into existing security, defense, and operational workflows, enabling rapid triage and decision‑making without manual data collection.
Target Audience
Primary customers include defense contractors, national security analysts, aerospace operators, autonomous systems developers, supply‑chain firms supporting critical infrastructure, and intelligence teams that rely on open‑source data for threat monitoring.
Features
- Continuous multilingual open‑source data collection covering local media, airspace notices, and regional activity logs
- Anomaly detection and cross‑source correlation engine that ranks signals by urgency, confidence, and source strength
- Structured JSON alert format delivered through a low‑latency REST API for easy integration
- Trend analysis indicating direction (e.g., increasing) and urgency level (e.g., elevated) for each detected indicator
- Capability to detect pre‑strike logistical and movement patterns as well as unusual clusters of restrictions and chatter