Sepsis remains a major cause of morbidity and mortality worldwide despite substantial advances in antimicrobial therapy and critical care. Early recognition and accurate risk stratification are essential for improving patient outcomes, yet current diagnostic approaches based on clinical assessment and organ dysfunction scores often fail to capture the complex biological processes underlying disease progression. In recent years, increasing attention has focused on integrating circulating biomarkers with established clinical scoring systems to support more precise and individualized management. Among emerging biomarkers, soluble urokinase plasminogen activator receptor (suPAR) and presepsin have demonstrated considerable promise because they reflect complementary aspects of the host response. While suPAR primarily represents sustained immune activation and overall disease burden, presepsin is closely associated with early innate immune activation following pathogen recognition. This review summarizes the current evidence regarding the biological characteristics, diagnostic performance, and prognostic value of these biomarkers and discusses their integration with established organ dysfunction models, including SOFA, qSOFA, NEWS2, APACHE II, and SAPS II. Available evidence suggests that combining suPAR and presepsin with clinical severity scores improves risk stratification, particularly among patients with intermediate clinical risk, and may facilitate earlier recognition of disease progression, more accurate prognostic assessment, and better-informed therapeutic decisions. The review also explores emerging developments in precision medicine, including artificial intelligence–assisted predictive models, electronic health record–based clinical decision support systems, and dynamic multimodal risk assessment. Furthermore, we propose the Integrated Sepsis Risk Pyramid (ISRP) as a conceptual framework that combines clinical evaluation, organ dysfunction scoring, and biomarker assessment into a stepwise strategy for bedside decision-making. Collectively, these advances support a transition from isolated biomarker interpretation toward integrated, biologically informed, and data-driven approaches that have the potential to improve personalized sepsis management and optimize outcomes in critically ill patients.