Simer: AI Developer Interviewing Platform

Simer is an AI interviewer for developer interviews. A candidate uploads their resume, the system analyzes it against the job description, and then generates a unique interview link. The candidate joins a one-on-one interview with an AI interviewer, which asks resume-aware and role-specific questions instead of using a generic script.
During the interview, the candidate may be asked to solve technical problems inside an embedded Monaco code editor. The AI uses the candidate’s code, explanations, transcript history, resume context, and job requirements to adapt follow-up questions. It looks at how the candidate breaks down the problem, reasons through tradeoffs, debugs mistakes, explains complexity, and whether the solution is brute-force or optimized for the role.
The system also collects camera-derived behavioral and integrity signals, such as attention and face-presence metadata, as supporting context rather than the main technical score. After the interview, Simer generates a transcript, technical scorecard, behavioral summary, and final decision card for recruiter review.
In the demo, we’ll show the actual codebase and the working interview flow: resume upload, interview-link generation, the AI interview session, the Monaco coding workspace, adaptive follow-up questions, and the final decision card.