Enterprise AI Chatbot Solution for University Websites

Artificial Intelligence (AI)-enabled chatbot solutions currently in place.
- The website-based chatbots are sourced from multiple vendors and have different capabilities and administrative controls.
- General Requirements
1. The chatbot should support a federated model where individual University departments can utilize the chatbot platform, each with its own bot. Chatbot knowledge should be able to be isolated or shared with other bots, as needed. This federated model should allow for central oversight by ITS but delegate individual chatbot administration to departments. Describe how this works.
2. Provide branding customization (UNCG logo, color scheme, greeting message, avatar/name, etc.) consistent with the University’s public-facing communication standards.
3. Describe how your solution interacts with a WordPress CMS system. Does the chatbot need to be installed on each individual webpage, or can it be installed on an entire departmental subdomain to ease the installation burden?
4. Does your platform support multi-channel deployment beyond a standard website (e.g. SMS, WhatsApp, MS Teams, native mobile apps) using the same central knowledge base?
5. Describe the customer’s interaction with the chatbot, including how the bot would appear on a University website, the greeting that a customer would receive, and how the bot converses with the customer.
6. The chatbot should be able to make use of content (e.g. webpages and related media / documents) on specified websites as well as additional information and documents that can be added to the chatbot’s knowledge base. Specify how the knowledge base is maintained, how often websites are crawled, etc.
7. Does your platform provide industry specific content prepackaged in the chatbot’s knowledge base? For instance, a Financial Aid chatbot may have information from crawled US Department of Education websites.
8. Can your solution review information available in the chatbot’s knowledge base against higher educationspecific knowledge metrics to proactively suggest when potential gaps in knowledge exist. Are there specific functional areas where this gap analysis exists? If so, specify which functional areas are included in the gap analysis capability.
9. In lieu of having a direct knowledge base support for a customer engagement, describe the generative AI capabilities for your solution.
a. How are these conversations flagged as potential knowledge gaps or specific conversations to review?
b. Describe how the generative AI answers can be confirmed to provide consistent answers across time.
c. Describe how the platform prevents hallucinations.
10. Describe how your solution supports multi-turn conversation capability (i.e., chatbot can ask clarifying followup questions when user intent is ambiguous). The chatbot should be able to maintain context throughout a customer engagement.
11. Proposed solutions should be compatibility with standard web browsers and mobile-responsive display formats.