Campus-Wide Enterprise Artificial Intelligence Platform

The Vendor is required to provide for a secure, enterprise grade, university campus-wide Artificial Intelligence (AI) platform designed specifically for higher education.
- Platform shall provide a unified, multimodel AI platform that supports teaching, learning, research, and administrative operations while ensuring strong data privacy, security, compliance, and responsible use.
- Platform that enables broad access to leading AI models through a single intuitive interface, supports collaboration across academic and administrative units, integrates with institutional systems, and aligns with the University’s AI Tools and Services Strategic Vision: University will use AI to power efficient operations and transformative academic and research experiences.
- Provide a secure, multi model AI platform that includes but is not limited to: software licensing, implementation, integration, training, support, and ongoing service for faculty, staff, and students across the University.
- AI systems shall be verified to produce fit-for-purpose outputs, be regularly monitored, and be updated as needed to perform reliably and generate accurate and complete results.
- Clear lines of accountability shall be established to an individual or group for decisions made using AI, with a human-in-the-loop where appropriate.
- AI systems and data used shall promote fair and equitable outcomes. Suppliers shall provide auditable documentation supporting bias detection, mitigation practices, and fairness assurance.
- AI systems and related processes shall be secure, safe to use, robust, and designed to prevent harm to individuals or the institution.
- Personal and University data privacy shall be respected. Authorized use, disclosure, and access shall comply with applicable privacy laws, governance policies, copyright, intellectual property, and other relevant regulations.
- Unified access to multiple leading AI models, including but not limited to:
•    ChatGPT
•    Claude
•    Gemini
•    LLAMA
•    Perplexity
- Seamless switching between models within a single interface
- Context retention when switching models
- Ability to compare outputs across multiple models for the same prompt
- Upload and analysis of content including but not limited to:
•    PDF files
•    Excel files
•    Word Documents
•    CSV files
•    Images
- YouTube video
- A centralized knowledge bank
- Drag-and-drop file management functionality
- Collaboration Tools
•    Group Chat functionality supporting multi-user and multi-bot conversations
•    Pre-configuration using custom knowledge sources
•    Department-wide AI bot sharing
•    A template library for rapid deployment
- Cost Optimization and Transparency
•    Demonstrated cost and token optimization capabilities
•    Usage monitoring and budget controls
•    Flexible pricing models (per-user and/or institutional)
•    Full pricing transparency with no hidden fees