This chapter provides an area to delve deeper into intelligent algorithms to detect patterns that can help in the early diagnosis of different types of disorders, classify the severity of the problems, and the actions for alleviating those concerns. This chapter also drives us to detect risks from patterns and markers by bringing to readers’ attention how different data sources can identify biomarkers leading to early detection of diseases. Readers are increasingly aware of the fact that mental data can be leveraged in proactive detection and early addressing of problems with timely interventions from caregivers. The primary objective of this chapter is to empower mental health-associated stakeholders with AI modeling tools and techniques. In addition, this chapter further extends its boundary by looking through the lenses of the essential plugins and components necessary for a risk framework under different scenarios. It explores the thorough use of diverse datasets and models brain scans and behavioral patterns. This chapter further allows us to evaluate GenAI and its role in assessing the severity of risks.