We believe the right connection can change your life, and at Mentorloop we make authentic human connections easier to find, build, and grow. We're always on the lookout for new technologies to help build great mentoring relationships, and naturally, we've turned our attention to AI - generative, non-generative, and agentic.
We would never use AI to replace an authentic mentoring relationship - we're not in the business of robot mentors! But we are excited about the potential for AI to support breaking the ice, setting an agenda, building momentum, optimizing connections, and generally removing friction in your mentoring journey. Here we answer a few frequently asked questions about how we use AI at Mentorloop.
What kind of AI are we talking about?
We are committed to experimenting with a breadth of AI technologies to find opportunities to support program coordinators and participants to get the greatest impact from their Mentorloop experience. This can take many forms, but most commonly this looks like:
Generative AI
Generative AI uses algorithms to create ("generate") content like text, images, audio, video, code etc. At Mentorloop we're using it to create text-based content - e.g. prompts to help start a conversation between mentor and mentee, or a match overview.
Non-generative AI
Non-generative AI analyzes existing data to make predictions, classifications, or recommendations. We use it to produce specific outcomes such as match scores, predict engagement patterns to optimize mentoring relationships, or recommend the most relevant content, resources, and next steps to both participants and program coordinators.
How does Mentorloop use AI?
Mentorloop uses AI to help both participants and program coordinators along in their mentoring journey. For mentors and mentees, it may appear as an option to generate an ice-breaker, help create an agenda for an upcoming mentoring meeting, recommend the most relevant resources, and offer 24/7 in-app support and guidance. For program coordinators, it can assist with program creation, management, and communication such as optimizing matching, analysing participant feedback, and recommending actionable next steps.
What AI features does Mentorloop have?
Mentorloop Intelligence includes the following features:
| Feature | What it does |
|---|---|
| Loopy | A chat assistant available on all screens for applicable participants, helping mentors and mentees navigate the platform, check on goals, and understand next steps |
| Coco | An AI assistant for program coordinators that can answer any question related to running a mentoring program |
| Smart Match Copilot | Helps program coordinators set up or adjust their matching rules and run our equitable Smart Match algorithm through a simple chat interface |
| Smart Match | AI-enhanced matching that understands free-text goals, skills, and aspirations, not just dropdown selections |
| Meeting Agendas | Suggests an agenda for an upcoming meeting, based on a pair's past meetings, shared notes, goals, skills, and expectations |
| Meeting Notetaker | Transcribes and summarizes a mentoring meeting from a live or recorded session, so both parties get a written record without having to take notes themselves |
| Survey Summaries | Summarizes participants' free-text survey responses once a survey closes, so coordinators can spot themes without reading every response individually |
| Match Rationale | Generates a plain-English explanation of why two people were suggested as a good match |
AI features are enabled or disabled for your program as a whole, rather than toggled individually. If you'd like to review whether AI is currently turned on for your account, or request that it be turned off, reach out to your Customer Success Manager.
Do I have to use AI in Mentorloop?
Our generative AI features are optional. In the platform, you'll see a button with this icon ✨ which offers AI-powered suggestions in context, like generating ice-breakers, meeting agendas, or a match overview. You can choose to click it and see what the AI proposes, or you can ignore it entirely.
Non-generative and agentic AI features that optimize the mentoring experience for both participants and program coordinators, such as matching analysis, work in the background to help you enjoy the most engaging and impactful mentoring journey. These AI features are available to all programs, but can be disabled by the program coordinator or at their request.
What if I don't want to use the AI features?
Many of our AI features are embedded into mentoring programs by default to ensure the best mentoring experience for everyone; however, program coordinators can opt-out of AI features in their program on behalf of themselves and their participants. Where AI features are enabled, program participants can choose whether to utilize generative AI features.
Where does my data go if I use the AI features?
To power your Mentorloop experience, we use AI across a range of features, workflows, and support. In doing so, we may use data such as profile information, goals, feedback, meeting history, etc., to deliver the most relevant and effective experience for both program coordinators and participants.
All AI processing happens inside Mentorloop's own AWS environment. Your data does not leave Mentorloop's ecosystem to reach a separate third-party AI company — everything runs on the same secure AWS infrastructure that already hosts the Mentorloop platform. We do not share personally identifiable information outside of Mentorloop, and your data is never used to train models for other customers or the general public.
We handle this data responsibly and in accordance with our Privacy Policy.
Do all programs on Mentorloop have these AI features?
No. Not all Mentorloop programs currently have access to our AI features. This is because program coordinators can elect to disable all AI features in their mentoring program, on behalf of themselves and their participants. It could also be because a new AI feature is in early release, and as such only available to a small subset of programs and participants.
For governance and compliance teams
If your organization needs to document Mentorloop's AI use for internal governance tracking, here's the short version:
- AI infrastructure provider: AWS, within Mentorloop's own environment
- Third-party AI model providers: None — all processing is contained within Mentorloop's AWS environment
- Data usage: Per-feature, primarily user-initiated; matching runs in the background but only within your own program's data
- Feature control: AI can be enabled or disabled for your organization as a whole, on request via Customer Success
If your organization needs formal documentation (e.g., a data processing agreement or AI governance attestation), please contact your Customer Success Manager and we'll provide the relevant paperwork.
If you'd like more information about how Mentorloop collects, processes, and stores your data, please check out our Privacy Policy.