Genus uses deferred acceptance algorithms to allocate talent across your organization — fairly, stably, and with zero blocking pairs guaranteed.
The best candidate doesn't always win — the most visible one does. Manual allocation is inherently flawed by human bias.
People end up in roles they didn't want and aren't suited for, leading to turnover, resentment, and lower overall productivity.
Nobody can explain why someone got a role over someone else. Decisions lack mathematical backing or provable fairness.
Deferred Acceptance (Gale–Shapley) is a matching algorithm that produces stable outcomes — meaning no candidate and role would mutually prefer each other over their current assignment.
Genus proves this on every single run, turning organizational design from an art into a provable science.
Set up your talent pool, run matching rounds, review and confirm assignments — all from one comprehensive, auditable dashboard.
Score candidates against vacancies with a structured fit-score system. Replace gut-feel rankings with standardized data inputs.
Rank your preferred roles using an intuitive drag-and-drop interface. Your preferences are taken seriously — the algorithm protects them.
Each organization has its own isolated data environment and independent matching pool.
Candidates rank available vacancies with a clean, frictionless drag-and-drop interface.
Every matching run reports critical economics metrics: blocking pairs, surplus, and assortativeness.
Admins maintain the power to confirm or override algorithm suggestions — with every decision securely logged.
Strict RBAC ensures OrgAdmin, Employer, Evaluator, and Candidate each sees only what they need.
Reproduce theoretical academic results directly in-app with highly configurable parameters.
Create your organization in minutes. Run your first provably stable match today.