Managed AI Infrastructure Empowering AI Initiatives

LLM access for all across universities, and flexibility for IT to control

Challenges in Higher Education

The capabilities and tools enabled by AI are advancing at an unprecedented pace. To keep pace with these changes, your IT strategy must be adaptable and responsive to the shifting ecosystem of AI infrastructure.

Security and Compliance Concerns

Protecting sensitive data and intellectual property is paramount in higher education. Our managed AI infrastructure prioritizes security to safeguard your university’s assets.

Managing AI Access and Costs

IT departments face challenges in tracking usage and controlling expenses related to AI. With varying tools, effective management of your AI infrastructure is crucial.

Ensuring AI Policy Compliance

Faculty need to ensure that students adhere to AI usage policies. This includes enforcing ethics, enabling reporting, and promoting learning over cheating.

Integration with Identity Management Systems

Managing access to a multitude of AI services, applications, and frameworks is complex. Current identity frameworks may not offer seamless access management for AI infrastructure.

Unsanctioned AI Tool Usage

The unauthorized use of AI tools by students and faculty can lead to risks such as intellectual property theft, copyright infringement, and data leaks.

Managed AI Infrastructure for Universities

Implementing AI policies across a diverse range of AI initiatives can be daunting. We have empowered numerous universities by building AI infrastructure that addresses their specific needs and challenges:

University-wide GPTs for Students and Faculty
API Support for University AI Projects and Applications
Customized AI Guardrails
AI Governance Frameworks
Cost Controls and Usage Throttling
Monitoring of AI Use Policies

Successful Customer Implementation: Generative AI at UChicago

At the University of Chicago, we successfully implemented our managed AI infrastructure, revolutionizing how faculty and students engage with AI technologies. This initiative has empowered the university to harness the potential of generative AI effectively and securely.

Solution deployed with Royal Cyber for 35,000 students to use at the same time.

Key Outcomes

Enhanced Collaboration: Faculty and students now have access to university-wide GPTs, promoting collaborative learning and innovation.
Robust AI Governance: Established AI policies ensure ethical usage and compliance, fostering an environment focused on learning rather than shortcuts.
Streamlined API Support: Our infrastructure provides seamless API integration for various university projects, enhancing efficiency and reducing time to market for new applications.

For more insights into this successful implementation, explore the full story here

Key Features and Benefits of Our AI Infrastructure

Private Connectivity: Deployed within a private network with private endpoints for AI services.
Capacity Management: Provides control over requests and tokens to efficiently manage AI service capacity.
Usage Tracking and Charge-Back: Enables monitoring of usage and allocation of costs to respective departments.
Resilient and Scalable Architecture: Built with Azure API Management to ensure scalability and reliability.
Observability: Offers detailed insights into performance, usage, and error tracking.
Hybrid Cloud Support: Deployable on Azure, on-premises, or other cloud environments.

Enterprise GPT Access: Secure user interfaces for accessing LLMs within the university network, fostering collaboration.
Vendor Agnostic Design: Flexibility to switch LLMs without modifying individual applications, ensuring versatility in your AI infrastructure architecture.
Centralized AI API Gateway: Provides shared AI services securely across various use cases within the managed AI infrastructure.
Seamless Azure Integration: Simplifies endpoint and key updates for existing applications to utilize the gateway effectively.
AI Routing and Orchestration: Manage and govern AI services based on priorities and target models.
Granular Access Control: Employs managed identities for enhanced security instead of master keys.

Why Choose Our Managed AI Infrastructure?

Securely Meet Diverse AI Needs

Address the varying AI requirements of all users, projects, and applications while maintaining robust security.

Simplify IT Management

Centralized control reduces complexity and enhances operational efficiency.

Future-Proof AI Infrastructure

Stay adaptable with an LLM-agnostic strategy to accommodate emerging AI models in your infrastructure for AI.

How to?

Dive into resources, check FAQs, and see our how-to guides.

Resources & Guides

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Pricing

Based on enterprise needs and the size of your institution.

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info@classbuddy.ai