What GNI decides and why. MAD Protocol outcomes, live threat verdicts, market implications, action recommendations, and blind spot warnings — the full intelligence output explained.
How GNI builds its evidence base over time. GPVS prediction accuracy, source weight evolution, pipeline run history, and the statistical methodology behind every intelligence claim.
The most honest assessment of GNI. Strengths, weaknesses, opportunities, and threats — analyzed rigorously with live prediction verification data showing exactly where GNI stands.
How GNI runs itself. All 4 GitHub Actions pipelines, the self-healing heartbeat, the 66-pattern security layer, and live token quota data proving .00/month L7 autonomous operation.
Intelligence should not be a privilege. It should be a right.
GNI_Autonomous was built to prove that industrial-grade AI intelligence can run for $0.00 per month, accessible to anyone in the world — including people in Myanmar where 61.1% of the population now has internet access (DataReportal 2025) but where even a $199/year subscription would represent 18% of average annual income.
Built as a Higher Diploma final project at Spring University Myanmar (SUM). The goal was never just to pass an exam. The goal was to build something real, something that keeps running after the exam is over, something that serves people.