AI-Enabled Admissions Communications and Automation Solution

The Vendor is required to provide AI-enabled admissions solution that supports and streamlines key components of the admissions lifecycle within an integrated systems environment, including (but not limited to) application intake, document processing and verification, eligibility evaluation support, workflow orchestration, compliance, and reporting.
- Core intake and verification
•    Pre-screening and requirements matching: real-time evaluation of application completeness and whether an applicant meets specific program prerequisites, with configurable rules, explainable outcomes, and clear staff review for exceptions (no automated admit and deny unless required)
•    Applicant inquiry and status support: 24/7 AI-assisted responses for applicant FAQs and proactive application and status updates to reduce staff email volume and improve service.
o    Automated payment and condition reminders: configurable reminders for outstanding application fees and payments and admission conditions (e.g., missing requirements), delivered through approved channels, with auditability and staff oversight
o    Automated applicant information requests: automated, template-based emails and messages to request missing or clarifying information from applicants based on pre-screening outcomes, with configurable triggers and appropriate staff review controls
•    Multilingual and accessible communications: support multilingual interactions and accessibility-aligned communications (vendor to describe supported languages and approach) 
•    Document intake, classification and OCR (staff-led verification): intake and classify applicant documents (e.g., transcripts, ids, study permits), extract data via optical character recognition (OCR) where applicable, and route exceptions to staff review queues 
•    Application and document pre-screening (staff-led verification and human-in-the-loop): AI assisted pre-screening to evaluate application completeness, required documents, and basic eligibility and prerequisite alignment at intake; flags missing and inconsistent information, generates explainable outcomes, and routes exceptions to staff review queues (no automated admit and deny unless required).
o    AI-assisted applicant ranking and categorization (human-in-the-loop): support configurable business processes such as ranking and categorizing applicants (e.g., by completeness, readiness, or risk flags) based on submitted application and document data. 
o    Outputs should be explainable and used to prioritize staff review queues (no automated admit and deny unless required)
- Workflow integration and strategic support
•    Document intake and OCR: AI-driven scanning, categorization, and data extraction from transcripts, ids, and study permits, with clear routing to staff review where required. 
•    Workflow and decision support (human-in-the-loop): triage, exception handling, identity verification flags, and transparent reasoning to support staff-led admissions decisions (no automated admit and deny) 
•    Fraud and duplicate management: leveraging AI to identify fraudulent documents and clean duplicate profiles within the sis 
•    International credential assessment: automated mapping of global grades to state equivalency standards 
•    SIS and CRM integration and data synchronization: map and synchronize applicant data, statuses, and supporting-document outcomes with colleague and recruit and CRM tool(s) to reduce manual re-entry and support end-to-end workflow continuity.
o    Provincial attestation letter (pal) automation: AI-assisted preparation, tracking, and status synchronization of pal requirements by province, including configurable workflows, audit trails, and integration points with institutional systems and (where applicable) provincial processes
•    Waitlist and yield forecasting: predictive analytics to manage seat capacity and prevent "melt" (students who drop before day 1) including:
o    Alternative program recommendations (conversion support): where an applicant is not eligible for a selected program, the solution should support recommending alternative programs aligned to the applicant’s submitted documents and prerequisite profile. 
o    Recommendations should be rules-aware, transparent, and subject to staff oversight
•    Transfer credit and RPL: mapping prior learning experiences to current curriculum modules 
•    Agent commission management: AI-assisted verification of international agent invoices against confirmed enrolments such as:
o    Agent contract expiry reminders: automated monitoring of agent contract end dates and key milestones, with configurable notifications and escalation to designated staff, and optional synchronization with CRM/SIS records.