MockOS is an AI-native interview operating system that simulates real interview conditions, evaluates candidates using structured rubrics, and produces objective readiness signals.
Readiness varies by panel, trainer, and intuition — not data.
Institutes and recruiters lack verifiable interview readiness metrics.
Trainer-led mocks are costly, inconsistent, and non-repeatable.
Role-specific interview flows designed to mirror real pressure and evaluation.
AI-based scoring across clarity, depth, accuracy, confidence, and consistency.
Interview flows are engineered, not generated randomly.
Signals improve as data scales across institutions.
Embedded between education and employment.
Training institutes, colleges, placement cells, staffing firms, and enterprises.
B2B-first adoption with recurring institutional usage.
Developed at Deployh’s AI Innovation Lab, Miyapur — focused on production-grade AI systems, not demos.