Pain Points & Solutions
Core pain points in university mental health
Starting from census efficiency, shortages of counseling resources, and crisis intervention, we build a campus safety system.
Inefficient psychological screening
Paper scales take too long to distribute, collect, and score; a census of 10,000 students can take weeks
A digital screening platform
Scan to assess, automatic scoring, and instant reports—a 10,000-student census finishes in 1–3 days
Counseling centers are understaffed
University counseling staff-to-student ratios are often below 1:4,000, and students wait weeks
AI assistant + human counseling
AI handles everyday counseling and psychoeducation, so counselors can focus on high-risk and in-depth cases
Crisis intervention comes too late
Crisis signals are scattered among counselors, peers, and residence staff, and are hard to detect in time
A multi-level alert system
Abnormal scale results, unusual AI conversations, and counselor feedback are fused, with automatic tiered alerts
Core Capabilities
Core capabilities
Prevention first, connecting a complete chain of screening, counseling, alerts, and intervention.
Psychological screening
Large-scale incoming-student and periodic mental-health censuses
- Batch assessment
- Automatic alerts
- Group reports
- Trend analysis
AI counseling assistant
24/7 intelligent psychological support
- Emotional support
- Crisis recognition
- Referral guidance
- Psychoeducation
Counseling management
End-to-end management for the counseling center
- Scheduling
- Counseling records
- File management
- Follow-up plans
Crisis alerts
Automatic detection of early risk signals
- Scale alerts
- Behavioral anomalies
- AI recognition
- Multi-level intervention
Technical Highlights
Technical highlights
AI conversation and data analysis, building a campus mental-health safety net.
AI mental-health assistant
LLM-based mental-health conversation, adapted to common student issues such as emotional distress, academic pressure, and relationships
Group psychological profiles
Automatically generates multidimensional group mental-health reports by school, year, and class to support management decisions and resource allocation
Privacy and compliance
Strictly separates anonymous screening data from identified intervention data, in line with student psychological-information protection rules