Community Mentors lets admins surface ibl.ai’s shared mentor library—such as subject-matter mentors built on OpenStax textbooks—inside their institution’s private mentorAI environment so learners can start chatting with them immediately.
It’s a fast, safe way to pilot or extend high-quality mentors without starting from scratch, while keeping configuration authority on your side (prompting, data attachments, model choice, and embedding).
Administrator · Instructor · Student (read-only access)
Browse a catalog that includes OpenStax-based course mentors, skills mentors, and other agents.
Learners can converse with Community Mentors but cannot change settings or configuration.
- Add or override a System Prompt
- Attach your own data (files/links) to localize content
- Switch the model powering the mentor
- Embed the mentor into your LMS/SIS or other systems
Turn on curated mentors quickly, then adapt them to programs or courses as needed.
- Go to Profile menu → Organization → Advanced → Community Mentors
- Toggle On to activate Community Mentors for your environment
- Open Explore to view the full catalog of community mentors now available
- Add OpenStax-based course mentors, skills mentors, or other agents to your environment
- System Prompt – Add/override to match your teaching voice or institutional guidance
- Attach Data – Connect your course materials to contextualize answers
- Switch Model – Choose the LLM that best fits your use case
- Embed selected mentors directly into your LMS/SIS or other systems so learners can access them in context
- Learners chat with Community Mentors right away but cannot alter prompts, data, or tools
Deploy subject-aligned mentors (e.g., Intro Biology, Economics) to provide immediate tutoring and Q&A.
Offer skills mentors (study strategies, writing help, career prep) across departments without building new agents from scratch.
Test mentors with select cohorts, then refine prompts/data and roll out broadly based on findings.
Embed mentors in course modules so students can get context-aware help alongside readings and assignments.
Start from high-quality shared mentors, then tailor prompts, datasets, and models to fit your policies and outcomes.
Once you complete these steps, you can pilot or extend high-quality mentors without starting from scratch—while keeping configuration authority on your side.