Enterprise AI Platform Implementation Services

The Vendor is required to provide enterprise AI platform that provides students, faculty, researchers, and staff across all institutions with access to approved AI capabilities through a shared technology foundation.
- AWS foundation and landing zone
• Assess and validate the AWS organization and account structure implemented by board, ensuring alignment to a centralized, multi-institution operating model and appropriate separation across environments
• Review the landing zone design, including security guardrails, logging, monitoring, and governance controls, and confirm readiness to support deployment
• Validate VPC and network architecture, including segmentation, connectivity, and access patterns required for the baseline platform
• Evaluate the infrastructure-as-code approach and provide recommendations focused on standardization, maintainability, and readiness
• Assess cost management capabilities, including allocation by institution and service and visibility into consumption
• Identify gaps and risks impacting delivery and provide prioritized recommendations
• Work with regental information systems (RIS) to implement agreed-upon changes necessary to support deployment
- Identity and access management
• Integrate the platform with board federated identity architecture, including Microsoft Entra id, existing SSO patterns, and institutional MFA controls, in coordination with RIS identity teams
• Implement a role-based access control model aligned to baseline platform capabilities, supporting system wide administration, institutional administration, and end-user roles
• Support group-based and attribute-based access mapping as required for the baseline solution
• Enable delegated institutional administration for assistants, knowledge repositories, and content, while RIS retains control of core identity services
• Ensure board retains centralized administrative control, including feature enablement, policy enforcement, and override capability
- AI platform deployment and configuration
• Assess the Boise state AI platform (agent core public stack) and deploy and configure the platform within the RIS-managed AWS environment
• Implement platform capabilities consistent with the Boise state baseline, including:
o Multi-model AI integration and centralized model management
o Assistant creation, management, sharing, and discovery
o Shared prompt libraries and reusable templates with administrative controls
o Knowledge-based assistants with document ingestion, source attribution, and role-based access control
o Administrative dashboards and standard configuration patterns
• Configure baseline observability capabilities, including usage analytics, reporting, and cost tracking by user, assistant, and institution
• Ensure implementation adheres to the Boise state reference architecture and avoids custom extensions beyond
- Operational readiness and transition
• Develop a platform operations model aligned to RIS ownership, including monitoring, alerting, and day-to-day management processes
• Define backup, recovery, and availability approaches appropriate to the baseline platform
• Establish cost management processes for ongoing visibility and control
• Structured knowledge transfer to RIS platform administrators, identity teams, and security operations teams
• Define and execute a transition plan from partner-led implementation to RIS operational ownership at the conclusion
• Recommendations for ongoing support and future enhancement approach to be considered in subsequent.