AI that screens and interviews engineers — probing real experience, adapting in real time, and generating a scored report before you even open your calendar.
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Ray doesn't just ask questions. It listens, evaluates the answer, and decides whether to probe deeper or move on — just like a seasoned interviewer would.
Interview rounds
Each round surfaces a different kind of signal. Pick the ones that matter for the role you're hiring.
15 minutes of focused project discussion. Validates whether candidates actually did what their resume says — ownership, end-to-end thinking, and real decisions made under pressure.
Calibrated to experience level and complexity tier. Not just "did they solve it" — but why this approach, what are the trade-offs, how does it scale under real load.
Open-ended design matched to your company stage and tech stack. Probes failure modes, scale bottlenecks, and real architectural decisions — not just the happy path everyone rehearses.
What makes it different
When a candidate says something interesting — or evasive — Ray digs deeper. Every answer shapes the next question.
Pulls from a repository, external sources, and AI-generated questions. Candidates can't prep for it. Your bar stays honest.
Skills can be faked. Lived experience can't. Every question ties to actual responsibilities from your job description.
Screening context flows into the full interview. No repetition, no starting over — just deeper evaluation every step.
Candidates speak their answers. AI questions are read aloud. The experience surfaces how people actually think under pressure.
Every session generates a scored evaluation with per-question ratings, strengths, weaknesses, and a hire/maybe/reject recommendation.
How it works
AI extracts must-have responsibilities, key skills, and role expectations — then suggests your interview settings.
Choose round type, experience level, and complexity. AI guides every choice with reasoning based on your JD.
Share a link. Adaptive probing runs automatically — no recruiter involvement needed.
Get a scored evaluation with full transcript, per-question ratings, strengths, weaknesses, and a final recommendation.
Early feedback
FAQ
Everything you need to know about Ray.
Ray uses a three-source question strategy: a curated repository, dynamically fetched questions from external sources, and AI-generated questions unique to each session. Even if two candidates get the same base topic, follow-up probes branch based on their specific answers — making every path unique.
The adaptive probing makes gaming extremely hard. Even if a candidate memorises an answer, the AI immediately follows up with "why that approach specifically?" or "what would break first at scale?" — questions that require genuine experience to answer credibly. Surface-level rehearsed answers get exposed quickly.
Ray reads your JD and suggests the right configuration — company stage, role seniority, experience level, and complexity tier. Each setting adjusts what questions are asked and how deeply the AI probes. A founding engineer interview at a 5-person startup looks very different from a staff engineer interview at a large company.
Yes — when a candidate moves from screening to a full interview round, Ray loads the screening report and uses it to calibrate. If the candidate showed strong system thinking in screening, the full round pushes harder. If there were gaps, those areas get revisited with more targeted questions.
Voice-first. AI questions are read aloud using natural text-to-speech. Candidates speak their answers, which are transcribed in real time. This creates a more natural interview feel — and often surfaces how candidates think under actual conversational pressure, which typed forms don't capture.
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