AI-Augmented Enrollment Engine • Triage Agent

Triage Agent

This dashboard shows how inbound enrollment demand is converted into action within minutes instead of hours: every message is intercepted, classified, routed, and answered (or escalated) with a documented next step. Teams get immediate coverage across email, web, text, social and phone without adding headcount for every volume spike.

In institutions running this workflow well, organizations typically see first-response times drop from multi-hour delays to under 5 minutes for routine inquiries, while human advisors focus on the highest-value conversations such as transfer credit, aid package review, privacy-sensitive cases and distressed students.

The result is better lead recovery, fewer dropped inquiries, higher counselor productivity, and more consistent service quality with traceable routing, confidence scoring, and CRM updates on every interaction.

FERPA-aware routing Omnichannel identity resolution Human heart, AI hands
Connecting intake stream…
Client
Inquiries Seen
0
Number of Agents
1 agent
State
Live
Controls Start, pause, restart, scale
Inquiries Intercepted
0
Across email, web, SMS, WhatsApp, social, and voicemail
Processed by Triage Agent
0
0 / min throughput
Auto Drafts
00%
Personalized response drafts with metadata
Human Handoffs
00%
FERPA, account-specific, security, specialist cases
Avg First Response (Equivalent)
Compared to a legacy baseline of 4h 00m
Under 5 Min Coverage
0%
Immediate acknowledgment or draft generated
Queue Backlog
0
Waiting for triage processing
Satisfaction Signal
composite
Composite score based on sentiment + response quality + timeliness

Flow

Animated packets show inquiries arriving from different channels and moving through triage.

No activity yet
Triage Agent
Intent • Policy • CRM • Drafting
0 active 0 queued
Auto Drafts
0
Human Handoffs
0
Packets animate from channel nodes into the Triage Agent, then route to auto-draft or human handoff outcomes based on the message metadata.

Live Message Processing

Current message, triage reasoning, and draft response streaming in real time.

Idle
No message selected
Audience
Program
Stage
Inbound Message
Waiting for traffic…
Identity Match
Language
Consent
Priority Signal
Agent State
Awaiting first message
Standby
Classifying intent Checking privacy/guardrails Preparing CRM updates Drafting response
Draft Response
Waiting for agent output

                
              

Throughput + Backlog

How quickly the agent keeps up with arriving inquiries.

When throughput stays ahead of arrivals, the queue stays flat and students get answers while intent is still high. When backlog grows, response delay compounds fast, increasing drop-off risk and advisor load later in the day.

Processed cumulative Backlog

Response Time Distribution + SLA Bands

Where completed work lands against response-time targets, split by auto drafts and human handoffs.

Auto draft Human handoff 5-min SLA cutoff Waiting for completed responses…

Auto-Draft vs Human Handoff

A balanced view: automation for routine questions, humans for privacy/sensitive cases.

Escalation Rate
0%

Routing Pressure

Top queues receiving traffic and specialist handoffs.

Impact Storyboard

Business-facing indicators that make the “black hole” problem visible and measurable.

Satisfaction Signal
Estimated Staff Hours Saved
0.0h
Compared to 4h baseline first-response cycle per inquiry
High-Intent Leads Surfaced
0
0% of processed
Activity Details

Message Detail