QuadC Early Alerts vs EAB Starfish

Both QuadC Early Alerts and EAB Starfish identify at-risk students based on key indicators like grades or attendance. QuadC Early Alerts uses a dynamic rules engine that allows administrators to define and assign specific weights to metrics pulled directly from your LMS or SIS. It calculates a risk score indicating how close a student is to falling below academic thresholds, triggering automated notifications for advisors and faculty.

EAB Starfish relies on a fixed risk model and fixed institutional analytics that are not updated in real-time. While it uses operational analytics to guide actions across identified student groups, it lacks the configurable, real-time risk scoring with institution-defined weighting that gives QuadC its agility.

Feature	QuadC Early Alerts	EAB Starfish
Configurable weighting
Real-time updates
Institution-defined factors
Historical trend modeling

Starfish relies heavily on manual faculty flagging, while QuadC automates alert creation based on LMS activity and student behaviour, ensuring no student slips through the cracks.

Feature	QuadC Early Alerts	EAB Starfish
Manual faculty flags
Automated LMS-driven alerts
Automatic case creation
Real-time intervention triggers

Identifying risk is only the first step. Both platforms provide structured workflows to manage interventions.

QuadC Early Alerts allows student support teams to enhance student profiles with structured action plans, key notes, and defined next steps. A case remains open until all action items in the plan are completed, ensuring complete accountability and follow-through. EAB Starfish offers comprehensive scheduling and case management, removing complicated barriers to modernize the campus intervention process. It aligns students with the exact resources they need while examining institutional capacity to support them.

Feature	QuadC Early Alerts	EAB Starfish
Action Plans & Next Steps Tracking
Ensure accountability (Cases stay open until resolved)
Resource alignment & capacity tracking

This is where the platforms diverge significantly in user experience and speed of insight. QuadC Early Alerts includes built-in AI that allows advisors and administrators to ask plain-language questions like, “Which students are at risk this week?” and receive immediate, data-backed answers. AI is directly connected to live LMS data, enabling faster decisions and on-the-fly adjustments to intervention strategies.

EAB Starfish relies on standard operational and strategic analytics dashboards. While powerful for structured reporting, it does not currently feature the same conversational AI interface for instant, on-the-fly data querying within the Starfish module.

Feature	QuadC Early Alerts	EAB Starfish
Conversational AI Data Querying
Transparent AI Triggers linked to LMS
Strategic Analytics Dashboards

While both platforms integrate with your existing Learning Management Systems (LMS) and Student Information Systems (SIS), the crucial difference lies in how data is used. QuadC syncs LMS data in real-time, feeding live student behaviours (like recent grades and attendance) directly into its dynamic risk scoring engine and conversational AI. This means an automated alert is triggered the moment a student misses a critical threshold.

EAB Starfish relies on standard integrations that focus on long-term strategic analytics. While the data is present, it lacks the real-time sync required to drive immediate, automated interventions.

Feature	QuadC Early Alerts	EAB Starfish
LMS Integration (Canvas, Blackboard, D2L, Moodle)
SIS Integration
Real-time LMS data sync
Data connected directly to AI insights

System adoption across your campus hinges on usability. QuadC is built with a modern, intuitive, and friendly user experience that minimizes the learning curve for faculty, advisors, and administrators, ensuring high daily engagement without extensive onboarding. In contrast, EAB Starfish relies on a more traditional, legacy interface that can feel dense and complicated, often creating friction for everyday users.

Feature	QuadC Early Alerts	EAB Starfish
Modern, intuitive interface
Minimal training required for faculty
Plain-language querying
Complex legacy navigation