Case Study

AI Case Management App for Student Risk Detection on ServiceNow

Built a GenAI-powered ServiceNow case management application that automatically detects at-risk students, generates explainable AI case summaries, and orchestrates structured advisor interventions through automated workflows, risk scoring, and a dedicated Advisor Workspace.

Business Challenge

• Higher education data was fragmented across Student Information Systems (SIS), Learning Management Systems (LMS), and financial platforms, making it difficult to identify at-risk students.
• Advisors relied on manual data collection and disconnected reports instead of a unified, actionable case management process.
• Risk signals lacked clear explanations, preventing advisors from quickly understanding why a student required intervention.
• Cross-department collaboration between advising, financial aid, and student support was uncoordinated, resulting in duplicate outreach and inconsistent case handling.
• A fully functional ServiceNow-native proof of concept had to be delivered within a fixed timeline before the ServiceNow Knowledge26 conference.

The objective was to:

• Build a ServiceNow-native AI case management application for early student risk detection.
• Integrate student and academic data from Neo4j to support automated risk evaluation.
• Automate at-risk student identification using deterministic risk criteria.
• Provide advisors with AI-generated, explainable case summaries and recommendations.
• Enable structured, cross-department intervention workflows through playbooks and automated case management.
• Deliver a working proof of concept before the ServiceNow Knowledge26 conference.

Solution

• Developed a dedicated ServiceNow scoped application extending Customer Service Management (CSM) for Early Alert case management.
• Integrated student and academic data from Neo4j through a static data ingestion pipeline.
• Built a deterministic risk scoring engine using 10 Decision Table criteria.
• Created a dedicated Advisor Workspace with a Daily Intelligence Brief and prioritized worklists.
• Implemented Now Assist to generate explainable AI case summaries and resolution notes.
• Designed 5 structured intervention playbooks with automated workflows, approvals, and conditional routing.
• Enabled cross-department collaboration across advising, financial aid, and student support teams.
• Configured SLA-based escalations, notifications, and a complete audit trail for every case.
• Connected external knowledge graph data through Neo4j and BurstIQ, aligned with the MCDS higher education data standard.

Key capabilities include:

• AI-powered student risk detection using 10 deterministic scoring criteria.
• Now Assist-generated plain-language case summaries and recommendations.
• Dedicated Advisor Workspace with Daily Intelligence Brief and prioritized case management.
• Specialized Student and Early Alert case data model built on ServiceNow CSM.
• Automated intervention playbooks with conditional routing and approval workflows.
• Cross-department collaboration across advising, financial aid, and student support teams.
• SLA-based case escalation, notifications, and complete audit trails.
• Integration with Neo4j and BurstIQ knowledge graph platforms.
• Support for 800-student representative dataset to demonstrate real-world risk detection workflows.

Business Impact & Value

Operational Impact

• Centralized student risk detection and case management within a single ServiceNow application.
• Automated risk evaluation using 10 deterministic criteria, eliminating manual report-based triage.
• Standardized advisor interventions through structured playbooks and workflow automation.
• Improved cross-department collaboration with shared case management and audit trails.
• Reduced manual effort by providing AI-generated case summaries and prioritized advisor worklists..

End-User Impact

• Advisors received prioritized daily worklists instead of manually reviewing multiple systems.
• AI-generated, plain-language case summaries helped advisors understand student risk faster.
• Structured intervention playbooks guided consistent and efficient case resolution.
• Cross-department collaboration provided a single, shared view of each student’s case.
• Students benefited from faster, more coordinated support and timely interventions.

Summary

Teiva Systems delivered a GenAI-enabled ServiceNow proof of concept that converts student risk signals into explainable early-alert cases and coordinated intervention workflows. Combining transparent rules-based scoring, Now Assist summaries, prioritized advisor worklists, and cross-department playbooks, the application demonstrates a practical path from fragmented data to earlier, more consistent student support—with human judgment at the center.

Talk with our experts

For USA

Raphael Holdermann

Co-founder & Chief Customer Officer at Teiva Systems USA

Raphael is a client-focused leader known for his big-picture business vision and entrepreneurial acumen, having successfully launched organizations, turned around challenged businesses and rapidly scaled programs for small to large enterprises in the ServiceNow ecosystem.

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Dach region (Germany, Switzerland & Austria)

Kostya Bazanov

Co-Founder & Director at Teiva Systems Germany

Kostya has been developing and extending the business footprint of Teiva Systems in the DACH region. Being a trusted advisor and a ServiceNow solution architect since 2012, he offers reliable and quality business and IT solutions, products, and services to our clients.

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Other countries

Oleksii Konakhovych

Co-Founder & CTO at Teiva Systems

Oleksii working with ServiceNow since 2007 and inspired by the opportunity to build a process design and platform architecture. Oleksii using a years of experience to be a few steps ahead of the challenges. Our customer will have the best result and noticeable improvements in the quality of work.

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