Strict privacy rules bottlenecked AI rollouts. Now, a hybrid self-service platform dynamically routes tasks by data sensitivity.
A major U.S. higher education institution operates one of the country's most powerful university supercomputers to support research and education for tens of thousands of students and staff.
The institution needed to deploy customized learning assistants and foundation models across campus but faced strict requirements around data privacy...
“When I talk to presidents and provosts around the country, I give them a very clear message: If you don’t do AI on your campus, the students are going to vote with their feet and go somewhere where they can learn this stuff, because they know it’s important to their futures.”
Public land-grant research university offering over 300 degree programs.
NVIDIA is a technology company that specializes in semiconductors, graphics processing units, and artificial intelligence for applications in data centers, gaming, and more.
University of Florida's Self-service computing portal is part of this use case:
Related implementations across industries and use cases
Large AI training jobs meant fighting for preemptible slots or leaving campus. Marlowe gave any lab guaranteed multi-node access on demand.
150+ siloed AI projects fragmented the campus. Standardizing on Copilot empowered students and staff to securely automate daily workflows.
Decades of data were buried in rigid keyword searches. Now, custom AI agents let the campus query millions of records in natural language.
Large AI training jobs meant fighting for preemptible slots or leaving campus. Marlowe gave any lab guaranteed multi-node access on demand.
Privacy risks held back AI for distributors. Amway now filters data in real time, deploying secure sales assistants in 15 days, not 35.
Deal data scattered across systems kept sellers from districts. AI unified it—leadership moved from retrospective reports to live intel.
Consultative selling couldn't scale. AI now tags thousands of meeting recordings to targeted skills so managers can actively coach.
Forty entities duplicated work, stalling claims for days. A global AI engine standardized workflows, cutting settlement time to one day.
Admin tasks bogged down 364k consultants. Copilot now drives 40M+ actions, reclaiming $150M in time for client advisory.
Strict privacy rules bottlenecked AI rollouts. Now, a hybrid self-service platform dynamically routes tasks by data sensitivity.
A major U.S. higher education institution operates one of the country's most powerful university supercomputers to support research and education for tens of thousands of students and staff.
The institution needed to deploy customized learning assistants and foundation models across campus but faced strict requirements around data privacy...
“When I talk to presidents and provosts around the country, I give them a very clear message: If you don’t do AI on your campus, the students are going to vote with their feet and go somewhere where they can learn this stuff, because they know it’s important to their futures.”
Public land-grant research university offering over 300 degree programs.
NVIDIA is a technology company that specializes in semiconductors, graphics processing units, and artificial intelligence for applications in data centers, gaming, and more.
University of Florida's Self-service computing portal is part of this use case:
Related implementations across industries and use cases
Large AI training jobs meant fighting for preemptible slots or leaving campus. Marlowe gave any lab guaranteed multi-node access on demand.
150+ siloed AI projects fragmented the campus. Standardizing on Copilot empowered students and staff to securely automate daily workflows.
Decades of data were buried in rigid keyword searches. Now, custom AI agents let the campus query millions of records in natural language.
Large AI training jobs meant fighting for preemptible slots or leaving campus. Marlowe gave any lab guaranteed multi-node access on demand.
Privacy risks held back AI for distributors. Amway now filters data in real time, deploying secure sales assistants in 15 days, not 35.
Deal data scattered across systems kept sellers from districts. AI unified it—leadership moved from retrospective reports to live intel.
Consultative selling couldn't scale. AI now tags thousands of meeting recordings to targeted skills so managers can actively coach.
Forty entities duplicated work, stalling claims for days. A global AI engine standardized workflows, cutting settlement time to one day.
Admin tasks bogged down 364k consultants. Copilot now drives 40M+ actions, reclaiming $150M in time for client advisory.