ibl.ai gives state university systems a single, AI-native platform to monitor at-risk students, coordinate interventions, and drive consistent retention outcomes — across every campus, every term.
State university systems face a compounding retention crisis. Students slip through the cracks not from lack of caring staff, but from fragmented data, inconsistent processes, and advisors stretched too thin to act in time.
Each campus runs its own early alert tools, case notes, and tutoring queues — creating silos that prevent system-wide visibility. A student struggling at one campus looks invisible to leadership at another.
Without a unified AI layer, retention reporting is always backward-looking. By the time dashboards surface a trend, the students it represents have already withdrawn.
Each campus uses different tools and thresholds for flagging at-risk students, making system-wide intervention impossible and leaving high-risk students undetected until it's too late.
Only 29% of flagged students receive a documented intervention within 7 days (EAB, 2023)Advisors at state systems manage 300–500 students each, making proactive outreach nearly impossible. Case notes are inconsistent, follow-ups fall through, and high-need students are lost in the queue.
Average advisor caseload at public universities: 441:1 (NACADA, 2022)Students transferring between system campuses encounter entirely different advising workflows, tutoring access, and support quality — eroding trust and increasing stop-out risk.
Transfer students are 2x more likely to stop out in their first term at a new campusSystem-level retention dashboards aggregate data weeks after the fact. By the time leadership identifies a cohort at risk, the intervention window has closed and the students have already left.
Institutions using lagging indicators miss 60%+ of preventable withdrawals (Civitas Learning)Tutoring demand spikes mid-semester but scheduling, matching, and utilization data live in disconnected systems. High-need students rarely connect with tutoring before their first failing grade.
Students who use tutoring in weeks 1–4 are 3x more likely to pass than those who start in week 8AI agents continuously monitor LMS activity, grade submissions, attendance signals, and financial aid flags across all campuses — surfacing at-risk students in real time with recommended intervention actions, not just scores.
Purpose-built AI agents triage incoming alerts, assign cases to advisors based on caseload and expertise, draft outreach messages, log follow-ups, and escalate unresolved cases — reducing manual coordination by over 60%.
MentorAI agents provide 24/7 personalized tutoring support, proactively engage students flagged by early alert, and route complex cases to human tutors — ensuring no student waits days for academic help.
A unified reporting layer aggregates intervention outcomes, tutoring utilization, and cohort retention rates across all system campuses — giving provosts and VP-level leaders actionable, real-time intelligence.
Deploy consistent AI-assisted advising playbooks across every campus while preserving local flexibility. Agents guide advisors through structured intervention protocols, ensuring equitable student experiences system-wide.
All AI agents run on your infrastructure. Student data never leaves your environment. ibl.ai is FERPA and SOC 2 compliant by design — with zero vendor lock-in and full institutional ownership of agents and data.
Map existing early alert tools, SIS data (Banner/PeopleSoft), LMS signals (Canvas/Blackboard), and advising workflows across all campuses. Establish data pipelines and define system-wide risk thresholds.
Deploy early alert monitoring agents, intervention case management agents, and MentorAI tutoring agents. Configure campus-specific thresholds and advisor routing rules within the shared system framework.
Run a supervised pilot with a defined student cohort across 2–3 campuses. Train advisors and student success staff on AI-assisted workflows. Calibrate alert sensitivity based on real intervention outcomes.
Expand deployment to all system campuses. Activate cross-campus retention analytics dashboard for system leadership. Establish quarterly AI performance reviews and continuous model improvement cycles.
Siloed tools per campus with inconsistent thresholds; alerts generated but rarely actioned in time
Unified AI agents monitor all campuses in real time, auto-triage alerts, and push actionable tasks to advisors within hours
Advisors manually track cases in spreadsheets or disconnected CRMs; follow-ups missed; no system-level visibility
AI agents manage case queues, draft outreach, log interactions, and escalate unresolved cases automatically
Students self-refer to tutoring after failing; high-need students least likely to seek help proactively
MentorAI proactively engages flagged students with personalized tutoring support before grades decline
Lagging reports produced monthly by IR staff; leadership acts on trends weeks after intervention windows close
Real-time cross-campus retention dashboard gives system leadership live cohort intelligence and intervention status
Wildly different advising quality, tutoring access, and support workflows depending on which campus a student attends
Standardized AI-assisted advising playbooks ensure equitable, high-quality support at every system campus
Provides 24/7 AI tutoring and mentoring agents that proactively engage at-risk students flagged by early alert systems, delivering personalized academic support before grades decline and reducing dependency on scarce human tutoring resources.
The core platform for building, deploying, and managing purpose-built AI agents for early alert monitoring, intervention case management, and retention reporting — all running on the institution's own infrastructure with zero vendor lock-in.
An AI-native learning management system that surfaces real-time engagement signals across all campuses, feeds early alert agents with behavioral data, and provides a unified student experience layer across the state university system.
See how ibl.ai deploys AI agents you own and control—on your infrastructure, integrated with your systems.