Calls dropped, records scattered—students started over at every handoff. Copilot transcription now carries the full picture through.
A public university with a mission of expanding access for first-generation learners, managing student engagement across voice, chat, email, text, and web with records fragmented across multiple disconnected systems.
With no single view of the student across systems, staff had to navigate multiple disconnected records to piece together context during each...
“Fragmentation creates invisible inequity. The burden shifts to the student to navigate complexity that should be managed by the institution.”
Public university offering undergraduate and graduate degree programs.
Enterprise software, cloud infrastructure, and consumer electronics platform.
California State University San Marcos's Student support is part of this use case:
Related implementations across industries and use cases
Working students lacked after-hours support. Now, AI agents resolve routine 24/7 queries, freeing staff to proactively guide enrollments.
Staff lost 570 hours/year moving data between systems. AI agents now parse handbooks to answer student inquiries 24/7.
Agents juggling 8+ tools struggled to keep pace. Now, AI handles 35% of chats, letting the team resolve complex issues 58% faster.
Agents split focus between members and manual note-taking. Now, an AI copilot summarizes calls, letting agents give their full attention.
120 managers manually pieced together context across 20 offices. AI now generates instant briefings for churn risks and handovers.
Consultative selling couldn't scale. AI now tags thousands of meeting recordings to targeted skills so managers can actively coach.
Working students lacked after-hours support. Now, AI agents resolve routine 24/7 queries, freeing staff to proactively guide enrollments.
Manually evaluating high call volumes was slow and inaccurate. Now, AI extracts sentiment so sales teams can refine their outreach.
Manual call evaluations delayed insights by weeks. Now, bots score calls at scale, empowering analysts to synthesize data in hours.
Calls dropped, records scattered—students started over at every handoff. Copilot transcription now carries the full picture through.
A public university with a mission of expanding access for first-generation learners, managing student engagement across voice, chat, email, text, and web with records fragmented across multiple disconnected systems.
With no single view of the student across systems, staff had to navigate multiple disconnected records to piece together context during each...
“Fragmentation creates invisible inequity. The burden shifts to the student to navigate complexity that should be managed by the institution.”
Public university offering undergraduate and graduate degree programs.
Enterprise software, cloud infrastructure, and consumer electronics platform.
California State University San Marcos's Student support is part of this use case:
Related implementations across industries and use cases
Working students lacked after-hours support. Now, AI agents resolve routine 24/7 queries, freeing staff to proactively guide enrollments.
Staff lost 570 hours/year moving data between systems. AI agents now parse handbooks to answer student inquiries 24/7.
Agents juggling 8+ tools struggled to keep pace. Now, AI handles 35% of chats, letting the team resolve complex issues 58% faster.
Agents split focus between members and manual note-taking. Now, an AI copilot summarizes calls, letting agents give their full attention.
120 managers manually pieced together context across 20 offices. AI now generates instant briefings for churn risks and handovers.
Consultative selling couldn't scale. AI now tags thousands of meeting recordings to targeted skills so managers can actively coach.
Working students lacked after-hours support. Now, AI agents resolve routine 24/7 queries, freeing staff to proactively guide enrollments.
Manually evaluating high call volumes was slow and inaccurate. Now, AI extracts sentiment so sales teams can refine their outreach.
Manual call evaluations delayed insights by weeks. Now, bots score calls at scale, empowering analysts to synthesize data in hours.