Unified Enrollment and Student Success Data Platform

Integrates CRM, ERP, LMS, and external outcomes data into a single analytics platform to support coordinated enrollment planning and student success decision-making.

The Problem

“Siloed enrollment and student success data prevents coordinated decisions”

Organizations face these key challenges:

1

CRM, ERP/SIS, LMS, advising, and external outcomes data use different identifiers and data definitions

2

Manual data reconciliation delays decisions by days or weeks

3

Enrollment and retention dashboards often describe historical trends but do not recommend action

4

Advisors and enrollment managers lack a unified student timeline across systems

5

Data governance, FERPA compliance, access control, and auditability are difficult across fragmented tools

Impact When Solved

Single trusted view of applicants, enrolled students, course activity, advising interactions, financial aid status, and outcomesEarlier identification of enrollment melt, course disengagement, stop-out risk, and advising needFaster cross-functional decision-making for admissions, student success, financial aid, and academic leadershipReduced manual reporting workload for institutional research and analytics teamsMore targeted student outreach, nudges, and support interventions

The Shift

Before AI~85% Manual

Human Does

  • •Export and combine CRM, SIS/ERP, LMS, advising, and outcomes data into shared reports
  • •Manually reconcile duplicate records and align student lifecycle stages across departments
  • •Define enrollment, retention, and success metrics for recurring dashboards and executive updates
  • •Review static reports to identify priority cohorts and decide outreach or intervention actions

Automation

    With AI~75% Automated

    Human Does

    • •Approve shared metric definitions, intervention policies, and data access rules
    • •Review prioritized cohorts and decide high-touch outreach or support actions
    • •Handle ambiguous record matches, unusual risk cases, and cross-department exceptions

    AI Handles

    • •Continuously unify cross-system records into a single student and prospect view
    • •Monitor enrollment, progression, and engagement signals to detect risk and opportunity cohorts
    • •Generate natural-language summaries, funnel insights, and recommended next actions for leaders and advisors
    • •Trigger policy-compliant tasks, case routing, and draft communications for human review

    Operating Intelligence

    How it works

    AI runs the first three steps autonomously.

    Humans own every decision.

    The system gets smarter each cycle.

    Confidence88%
    ArchetypeRecommend & Decide
    Shape6-step converge
    Human gates1
    Autonomy
    67%AI controls 4 of 6 steps

    Who is in control at each step

    Each column marks the operating owner for that step. AI-led actions sit above the divider, human decisions and feedback loops sit below it.

    Loop shapeconverge

    Step 1

    Assemble Context

    Step 2

    Analyze

    Step 3

    Recommend

    Step 4

    Human Decision

    Step 5

    Execute

    Step 6

    Feedback

    AI lead

    Autonomous execution

    1AI
    2AI
    3AI
    5AI
    gate

    Human lead

    Approval, override, feedback

    4Human
    6↺ Loop
    AI-led step
    Human-controlled step
    Feedback loop
    TL;DR

    AI handles assembly, analysis, and execution. The human gate sits at the decision point. Every cycle refines future recommendations.

    The Loop

    6 steps

    1 operating angles mapped

    Operational Depth

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