People decisions,with context.
PairScore supports institutions making complex people-centered decisions where quantitative measures alone are not enough. The capability running today is mentorship matching: a whole participant pool paired in a single run, on shared experience themes and capacity rather than on whoever replied to the email first.
Institutional Solutionson one framework.
PairScore can support institutions making complex people-centered decisions where quantitative measures alone are not enough. Here is what runs today and what is being built. The status on each row is the honest one.
- Mentorship matchingAvailable
- A whole participant pool matched in one pass on shared experience themes and growth opportunities, with mutual requests protected.
- Capacity-aware matchingAvailable
- Mentor capacity and role rules are enforced by the run, not checked afterwards, and Capacity Utilization reports what the cohort actually absorbed.
- Compatibility analysisIn development
- The same dimensional comparison applied to your own pools, for pairings and groupings beyond mentorship.
- Applicant reviewIn development
- Structured, explainable comparison of applicants against a program's stated mission and priorities.
- Advising and student supportIn development
- Alignment context an advisor can open in a meeting, with the reasoning attached rather than a number to defend.
- Residency readinessIn development
- Readiness and application preparation support for students moving to the next stage.
- Cohort analysisIn development
- Patterns across a cohort rather than one profile at a time, for programs deciding where to put support.
- Custom decision-support modelsIn development
- The framework configured for a decision specific to your institution.
One run.Not one at a time.
Match Runs
A Match Run proposes a complete set of pairings using stable matching, so no two people would both rather have swapped. Mutual requests are given priority, and an AI-enriched shortlist pass evaluates the strongest candidates for each mentee. You get the pairings and the numbers behind each one. You still approve them.
Match Run · Sample cohort
Completed
- Total pairs
- 34
- Capacity Utilization
- 82%
- Avg match score
- 78
- Unmatched
- 3
- MEN-118MTE-042matched to each other. Mutual request.Mutual request92
- MEN-104MTE-017matched to each other. Shared theme: rural health.Shared theme: rural health88
- MEN-131MTE-055matched to each other. Shared theme: translational research.Shared theme: translational research84
- MEN-127MTE-009matched to each other. Capacity 2 of 3 used.Capacity 2 of 3 used71
Illustrative example. Sample run, not a real cohort.
Four steps.Not four weeks.
- 01
Upload the pool
Mentors and mentees together, with their capacities and their role rules. One import, not one spreadsheet tab per cohort.
- 02
Configure the run
Set mentor capacity, decide whether mutual requests take priority, and choose whether the AI shortlist pass runs over the strongest candidates.
- 03
Execute the Match Run
Stable matching runs across the entire pool at once, so a good pairing late in the list does not lose to a mediocre one made early.
- 04
Review, rematch, export
Every pair comes with its score and its reasoning. Rematch by hand where you disagree; the engine blocks substitutions that break capacity or your role rules rather than accepting them quietly.
Numbers to report.And one we withhold.
Run analytics
Total pairs, average match score, Capacity Utilization, participants left unmatched and the reason each one was left out. What no honest system can give you is proof that the mentorship caused an admissions outcome. PairScore will not manufacture that figure to make your annual report look better.
Match Run · Sample cohort
Completed
- Total pairs
- 34
- Capacity Utilization
- 82%
- Avg match score
- 78
- Unmatched
- 3
- MEN-118MTE-042matched to each other. Mutual request.Mutual request92
- MEN-104MTE-017matched to each other. Shared theme: rural health.Shared theme: rural health88
- MEN-131MTE-055matched to each other. Shared theme: translational research.Shared theme: translational research84
- MEN-127MTE-009matched to each other. Capacity 2 of 3 used.Capacity 2 of 3 used71
Illustrative example. Sample run, not a real cohort.
Three terms your teamwill use every cycle.
The product's own definitions, unedited, as they appear inside the institution portal.
- PairScore
- Your overall compatibility score for a mentor-mentee match based on factors such as shared goals, interests, communication preferences, experiences, mentorship needs, and overall alignment patterns. The score is designed to provide a more holistic view of mentorship fit beyond just surface-level similarities.
- Capacity Utilization
- Shows how much of the available mentor capacity is currently being used within a match run or cohort.
- AI Alignment
- Uses AI to evaluate the quality of a mentor-mentee match relative to other possible pairing combinations within the participant pool.
Send your list.See the run.
Tell us how large your cohort is and how you match today, and we will walk you through what a Match Run would return.