For professors

Find the right student — not 400 cold emails.

Post a funded MSc or PhD seat. Receive a small, ranked shortlist of motivated international applicants — every one with a verified academic profile, a paper list, and a personalised note tied to your recent work. No bulk-blast, no agents.

In pilot conversations with faculty at the University of Alberta, University of Toronto, University of Maryland, Simon Business School (University of Rochester), and Flinders University.

End the inbox flood

Replace hundreds of off-target cold emails with a ranked shortlist of 5–10 applicants who actually fit.

Pre-screened, mentor-shortlisted

Every applicant has a verified academic profile and a mentor-review note before they reach you.

Reach talent agents never see

Students in the global South who would not otherwise apply — but absolutely meet the bar.

Faculty dashboard · preview

Your open positions, your shortlist.

Funded MSc · Edge ML
12 pre-screened

Mentor-shortlisted applicants (sample):

Ayesha R.
Dhaka, Bangladesh · CGPA 3.78 · IELTS 7.5
mentor-shortlistedfit 0.92
  • · Quantised on-device LMs — undergrad thesis, 2024

“Read your NeurIPS '24 paper; building edge-deployable Bengali NLP at university lab.”

Imran K.
Lahore, Pakistan · CGPA 3.85 · IELTS 7.0
mentor-shortlistedfit 0.88
  • · Federated NLP for low-bandwidth networks (workshop, 2024)

“Already running federated NLP experiments on cheap Android hardware.”

Mary O.
Lagos, Nigeria · CGPA 3.91 · IELTS 8.0
mentor-shortlistedfit 0.86
  • · On-device speech recognition for Yoruba (preprint, 2025)

“Building offline speech tools for low-resource African languages.”

Tanvir H.
Chittagong, Bangladesh · CGPA 3.74 · IELTS 7.5
mentor-shortlistedfit 0.81
  • · Pruning techniques for mobile transformer inference (2024)

“Strong engineering record, less publishing — solid MSc candidate.”

Post a funded position

Tell us what funding you hold and who you'd love to supervise.

We'll surface your seat to students whose academic profile actually fits, with mentor review before any applicant reaches you. Preview form — onboarding happens 1:1 during the pilot.

Preview form. Nothing is posted publicly during the pilot.

What you receive

A small shortlist — not a flood.

Each applicant arrives with a verified academic profile, a paper list, and a personalised note that quotes your recent work. You decide who advances.

Ayesha R.
Dhaka, Bangladesh · CGPA 3.78 · IELTS 7.5
mentor-shortlistedfit 0.92
  • · Quantised on-device LMs — undergrad thesis, 2024

“Read your NeurIPS '24 paper; building edge-deployable Bengali NLP at university lab.”

Imran K.
Lahore, Pakistan · CGPA 3.85 · IELTS 7.0
mentor-shortlistedfit 0.88
  • · Federated NLP for low-bandwidth networks (workshop, 2024)

“Already running federated NLP experiments on cheap Android hardware.”

Mary O.
Lagos, Nigeria · CGPA 3.91 · IELTS 8.0
mentor-shortlistedfit 0.86
  • · On-device speech recognition for Yoruba (preprint, 2025)

“Building offline speech tools for low-resource African languages.”

Tanvir H.
Chittagong, Bangladesh · CGPA 3.74 · IELTS 7.5
mentor-shortlistedfit 0.81
  • · Pruning techniques for mobile transformer inference (2024)

“Strong engineering record, less publishing — solid MSc candidate.”

Onboard your lab

Stop sorting cold emails. Start meeting students who fit.

  • 5–10 mentor-shortlisted applicants per seat
  • Pre-verified profiles, papers, English scores
  • No bulk-blast outreach, ever
  • Free during the pilot
Onboard your lab

Preview form. Nothing is posted publicly during the pilot.