At Colaberry, we didn’t set out to build just another chatbot.
We wanted something deeper.
A system that talks to students the way a mentor would—at the right moment, with the right words, and with the right level of care.
So we trained our AI to do just that.
The result?
An early-warning system that doesn’t just track disengagement—it responds to it with empathy and context. And it’s changed the way we support our learners.
The AI doesn’t wait for someone to ask for help.
It constantly analyses:
Login frequency
Assignment progress
Missed deadlines
Drop in class attendance
Even behaviour like repeated video rewatches (a sign of struggle)
Based on this data, it identifies patterns that usually lead to dropouts or disengagement—and acts before it’s too late.
Here are real examples of how our AI engages students at critical points:
Case 1: Missed 2 sessions back-to-back
"Hey Priya, we noticed you missed your last two live sessions. Everything okay? If you're stuck or overwhelmed, we're here to help. You can always reach out or check out the quick replay. We believe in you."
Case 2: Logged in regularly, but no recent assignment submission
"Hi James, you're logging in regularly—great job staying consistent! We noticed you haven’t submitted Module 3 yet. If you’re facing challenges or just need a little push, let us know. You've come this far—don’t stop now."
Case 3: Sudden drop in activity after high engagement
"Hey Marcus, we’ve been impressed with your progress so far. Noticed a sudden pause—everything okay on your end? Even if life’s gotten busy, small steps can keep the momentum going. Let’s get back on track together."
They may seem small—but they’re incredibly powerful.
Students feel seen—not just like a number on a dashboard.
The tone is supportive, not robotic—based on what’s happening in their journey.
Many reply directly to these messages, starting conversations they otherwise would’ve avoided.
And most importantly:
These nudges have helped us reduce silent dropouts and improve overall engagement rates dramatically.
Everything the AI says is modeled after the way great mentors talk:
It reassures, without scolding
It notices effort, not just output
It meets students where they are—whether they’re flying or falling behind
We trained the system using years of human interactions, FAQs, and real mentor advice. That’s why it feels personal—because it is.
If you're a university, bootcamp, or school:
Imagine a system that checks in with every student—without adding a single new staff member.
You’ll catch red flags early, open up more support conversations, and give your human mentors time to focus on students who really need 1-on-1 care.
It’s not about replacing people.
It’s about scaling care—with the help of smart systems.
Book a free strategy call now