Nov 5, 2025
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B2C Case Study
Leading UK University Reduced Student Call Wait Times by 99% With Emergent’s AI Phone Agent
Leading UK University Reduced Student Call Wait Times by 99% With Emergent’s AI Phone Agent
North London Metropolitan University cut student call wait times by 99% using Emergent’s AI phone agent, automating 85% of inquiries with full GDPR compliance.
Arya Chandra
Call wait times reduced
Inbound inquiries automated
Faster tour bookings
GDPR & UK privacy compliance
Use case
Challenge
Solution
Outcome
North London Metropolitan University (NLMU), a major UK public institution serving over 30,000 students and partnering with organizations such as TfL and Ocado, was struggling to keep up with surging call volumes and long student wait times.
To overcome this challenge, NLMU implemented Emergent, a multi-agent, enterprise-grade AI phone system that completely automated its frontline communications.
As a result:
Average call wait times dropped from 18 minutes to under 2 seconds.
85% of inbound inquiries were automated.
Live CRM bookings were handled autonomously.
All interactions were conducted under 100% GDPR and UK privacy compliance.
Use case
Challenge
Solution
Outcome
North London Metropolitan University (NLMU), a major UK public institution serving over 30,000 students and partnering with organizations such as TfL and Ocado, was struggling to keep up with surging call volumes and long student wait times.
To overcome this challenge, NLMU implemented Emergent, a multi-agent, enterprise-grade AI phone system that completely automated its frontline communications.
As a result:
Average call wait times dropped from 18 minutes to under 2 seconds.
85% of inbound inquiries were automated.
Live CRM bookings were handled autonomously.
All interactions were conducted under 100% GDPR and UK privacy compliance.
Use case
Challenge
Solution
Outcome
North London Metropolitan University (NLMU), a major UK public institution serving over 30,000 students and partnering with organizations such as TfL and Ocado, was struggling to keep up with surging call volumes and long student wait times.
To overcome this challenge, NLMU implemented Emergent, a multi-agent, enterprise-grade AI phone system that completely automated its frontline communications.
As a result:
Average call wait times dropped from 18 minutes to under 2 seconds.
85% of inbound inquiries were automated.
Live CRM bookings were handled autonomously.
All interactions were conducted under 100% GDPR and UK privacy compliance.
Use case
Challenge
Solution
Outcome
North London Metropolitan University (NLMU), a major UK public institution serving over 30,000 students and partnering with organizations such as TfL and Ocado, was struggling to keep up with surging call volumes and long student wait times.
To overcome this challenge, NLMU implemented Emergent, a multi-agent, enterprise-grade AI phone system that completely automated its frontline communications.
As a result:
Average call wait times dropped from 18 minutes to under 2 seconds.
85% of inbound inquiries were automated.
Live CRM bookings were handled autonomously.
All interactions were conducted under 100% GDPR and UK privacy compliance.
Conclusion
By integrating Emergent’s multi-agent AI system, North London Metropolitan University transformed its student services from a high-cost, overburdened call center into a 24/7 intelligent support system that is faster, compliant, and highly scalable.
Emergent not only improved efficiency but also freed human staff to focus on student success and strategic growth, setting a new benchmark for how higher education institutions can modernize their service operations with AI.
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