the DIY way
- Respond to individual complaints
- Spend hours figuring out what is happening
- Depend on students to report issues
- Repeat the same guidance over and over
- End with scattered feedback and guesswork
Chat-based AI support for student teams
give ongoing tailored support, gain early visibility into challenges, step in only when needed.
Only 3 spots • takes 2 minutes
Research-basedResearch-backed Student-tested Instructor-informed
The Problem
we divided the work...but never worked together.
can I talk to you after class about my group?
everyone was too polite to bring it up.
The Solution
Quick chat-based check-ins to help teams get support early and give instructors clear signals only when relevant.
How it works
Students join through a link, complete a short onboarding, and get ongoing check-ins and support.
Short onboarding, Orb learns strengths, expectations and ways of working.
Private or team assistance to clarify, plan, or work through challenges.
Quick check-ins reveal changes in alignment in key areas.
We've detected a pattern of uneven workload across recent check-ins.
Instructors get clear, actionable insights into teams that need attention.
Who it's for
Founding Pilot
Free pilot designed to test whether Orb creates real value for student teams.
Share project context in 25 minutes. Orb prepares your course link.
Students join by link with their teams. Orb builds a baseline of how they work.
Orb checks in and supports teams early. You see signals when attention may help.
FAQ
Yes. Students can use Orb privately to reflect, ask for guidance, raise a concern, or prepare for a difficult conversation.
Teams can also use Orb together to clarify goals, structure discussions, organize work, and work through collaboration challenges.
No. Orb does not read or monitor students' existing Telegram conversations.
It works only with information students intentionally share with Orb and interactions that happen directly through Orb.
Instructors do not receive students' raw private conversations.
Orb surfaces concise, team-level signals when instructor attention may be useful, for example, an emerging workload issue, what Orb has already done to support the team, and why additional support may be needed.
Not every difficulty is escalated. Orb supports students directly where appropriate, with visibility and escalation rules agreed during pilot setup.
No. Orb supports collaboration, reflection, and teamwork.
It is not designed to grade students or automatically determine academic performance.
Initial setup is designed to be lightweight. We configure the course and project context with you, while Orb handles student-facing onboarding and ongoing interactions.
No LMS integration is required for the founding pilot.
During the pilot, we may ask for brief feedback and an end-of-pilot discussion to understand what worked and what should improve.
Before the pilot begins, participation, consent, instructor visibility, escalation procedures, and data-management processes are agreed with the participating institution and communicated clearly to students.
Orb does not expose students' raw private conversations to instructors.
Where participation is optional, students are told how opting out works and how it affects pilot or course-related activities. Specific procedures depend on institutional and course requirements.
You'll receive a summary of what we learned, including relevant observations from the pilot and opportunities for improvement.
Founding pilot partners can continue contributing to Orb's development if they'd like, but there is no obligation to continue using Orb after the pilot.
Join us!
Tell us a little about your team-based projects.