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
Decades of data were buried in rigid keyword searches. Now, custom AI agents let the campus query millions of records in natural language.
Staff were too busy for AI seminars. Now, student ambassadors help them build custom Copilot agents, cutting reporting hours to minutes.
Manual data cleaning and report drafting bottlenecked workflows. Now, faculty and staff use Copilot to synthesize research and speed admin.
Privacy risks held back AI for distributors. Amway now filters data in real time, deploying secure sales assistants in 15 days, not 35.
Feedback lagged for 15 seconds. Switching to specialized hardware cut response times to two seconds while halving costs.
Working students lacked after-hours support. Now, AI agents resolve routine 24/7 queries, freeing staff to proactively guide enrollments.
Agents juggling 8+ tools struggled to keep pace. Now, AI handles 35% of chats, letting the team resolve complex issues 58% faster.
With 99% of records missing metadata, teams sifted unlabeled databases. Now, AI generates column descriptions for data experts to verify.
Manual document summaries bottlenecked experienced staff. Now, AI drafts preliminary risk assessments, freeing teams for complex 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
Decades of data were buried in rigid keyword searches. Now, custom AI agents let the campus query millions of records in natural language.
Staff were too busy for AI seminars. Now, student ambassadors help them build custom Copilot agents, cutting reporting hours to minutes.
Manual data cleaning and report drafting bottlenecked workflows. Now, faculty and staff use Copilot to synthesize research and speed admin.
Privacy risks held back AI for distributors. Amway now filters data in real time, deploying secure sales assistants in 15 days, not 35.
Feedback lagged for 15 seconds. Switching to specialized hardware cut response times to two seconds while halving costs.
Working students lacked after-hours support. Now, AI agents resolve routine 24/7 queries, freeing staff to proactively guide enrollments.
Agents juggling 8+ tools struggled to keep pace. Now, AI handles 35% of chats, letting the team resolve complex issues 58% faster.
With 99% of records missing metadata, teams sifted unlabeled databases. Now, AI generates column descriptions for data experts to verify.
Manual document summaries bottlenecked experienced staff. Now, AI drafts preliminary risk assessments, freeing teams for complex advisory.