<aside>

Demo | Code | Principles & Methodologies

</aside>

Job seekers today face a brutal paradox: their resumes must please both algorithms and humans, while interviews demand confidence under pressure. Even qualified candidates are caught in this double bind—forced to strategize for machines in writing, then perform for people in person. The system shouldn’t work this way, but it does: talent gets filtered out by automated screenings, while live interviews reward polish over potential.

Applicant Sensei aims to tackle this barrier head-on. With AI-powered resume tuning and stress-tested interview drills, it doesn’t just prepare candidates—it hacks a broken process, ensuring skills speak louder than formatting or nerves.

Key Features

Smart Resume Analysis

• Identifies missing keywords from job descriptions
• Scores resume readability using ATS (Applicant Tracking System) benchmarks
• Suggests skill-based improvements (e.g., “Add ‘project management’ to highlight team leadership”)

Adaptive Interview Simulator

• Adjusts question difficulty based on user performance
• Provides real-time feedback on:
  • Speech clarity (pace, filler words)
  • Answer structure (using STAR method framework)

Target Users

• Recent graduates navigating competitive entry-level markets
• Career-changers requiring strategic rebranding
• Neurodiverse candidates benefiting from simulated social scenarios
• HR teams seeking standardized evaluation frameworks