RFP Description
The vendor is required to provide a artificial intelligence academic sales training software that include:
- Integration capabilities with third-party identity providers.
- Compliance with recognized standards (e.g., NIST, FIDO).
- Explain all authentication methods for administrative access. Include password policies, SSO support, and any additional security layers or protocols.
- Describe the process for creating and presenting a user portal that allows users to request and/or assign addresses. Include:
• Steps involved in portal setup and configuration.
• Customization options for branding and user interface.
• Workflow capabilities for request and approval processes.
• Security measures and authentication methods for portal access.
• Integration options with existing systems or directories.
- Detail all options for importing configuration data from other systems or vendors. Include supported formats, migration tools, and any limitations or prerequisites.
- Explain how RBAC is implemented. Include:
• Levels of granularity (e.g., user, group, role).
• Customization options for roles and permissions.
• Any predefined roles or templates available.
- Describe how AI is incorporated into your solution. Include:
• Types of AI used (e.g., NLP, Machine Learning, Generative AI).
• Specific functions supported by each AI type.
• How models are trained, updated, and monitored for bias or ethical compliance.
- Provide detailed specifications for physical requirements (rack space, power, cooling). 
- List all connectivity needs (e.g., Ethernet, fiber, speed requirements). Include redundancy options and compatibility with common standards.
- Explain how APIs are used in your solution. Include:
• Available endpoints and supported functions (e.g., monitoring, reporting)
• Authentication and security measures for API calls.
• Availability of documentation and developer support"
• Describe how your solution integrates with ICON (Canvas), including authentication method (HawkID SSO vs separate login), gradebook synchronization, and any technical requirements for linking AI engagement scores to course assessments
- Specify the typical lead time required to assemble a professional services team for deployment. Include factors that may affect scheduling and any expedited options.
- Describe whether your solution offers a pilot or test period (e.g., one semester) Include:
Duration and scope of the pilot period.
- Explain data retention policies and configurability. Include default retention periods, options for extension, and compatibility with external storage solutions.
- Specify the maximum number of interactions (e.g., simulations, quizzes) supported per student per course or semester. Include any limits or scalability options.
- Describe whether faculty can create content using AI (e.g., conversational input). If not, explain the process and timeline for company-assisted content creation. Include any tools or templates provided.
- Explain how grading of AI-driven interactions can be linked to institutional gradebooks. Include integration methods, automation options, and supported LMS platforms.
- Describe avatar capabilities (animated vs. audio-only). Include customization options for appearance, gestures, and voice.
- Specify how long scoring data is retained and whether retention is configurable. Include any export options for archival purposes.
- Describe how licenses are structured (e.g., per student, per semester). Include whether licenses can be transferred between terms and any volume discount options.
- Are there license add-ons that require more tokens, for example, or are the licenses all-inclusive of all features?
- Supplier to address if a student "license" must be a named user or if it can be a concurrent user license, like if a student drops out of a course, would another student be able to take up that license?
- Explain billing process Include flexibility, invoicing details, and any integration with university billing systems
- Identify how long a student may access the software over their entire time at UI regardless of how many courses they may access this software for while a student.
Timeline

RFP Posted Date: Saturday, 31 Jan, 2026
Proposal Meeting/
Conference Date:
NA
NA
Deadline for
Questions/inquiries:
Sunday, 08 Feb, 2026
Proposal Due Date: Monday, 02 Mar, 2026
Authority: Government
Acceptable: Only for USA Organization
Work of Performance: Offsite
RFP Budget: NA
Contract Term: NA
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