Cloud workloads waste up to 60% of their allocated resources because today’s autoscalers react too late or predict poorly. SYDA introduces a new paradigm — synaptic autoscaling. Inspired by neural learning, SYDA continuously adapts to workload patterns, proactively right-sizing compute before demand shifts occur. It connects seamlessly to existing telemetry without code changes or data exposure, working across major cloud providers. In live environments, SYDA has demonstrated up to 60% cost savings while maintaining strict SLOs. Developed from advanced research in self-adaptive systems, SYDA turns cloud scaling into a self-learning, performance-driven process.