Adaptive AI interviews, structured technical assessments, scenario-based reasoning, and client-side AI proctoring — combined into a single evaluation engine that helps hiring teams see the whole candidate.
The AI conducts a natural, spoken interview — dynamically choosing its next question based on what the candidate just said, the requirements of the role, and the skill level they've already demonstrated. No two interviews follow the exact same script.
Each response shapes the next question — the AI probes deeper on strong answers and redirects when a topic runs thin, the way a skilled interviewer would.
Questions are calibrated to the job requirements loaded for that assessment, so a senior backend role and a junior support role never get the same interview.
As a candidate demonstrates fluency, the AI raises the bar on follow-ups; when answers are shallow, it stays foundational instead of overreaching.
Simulated demonstration — not a live model response
Knowledge checks, domain-specific technical questions, and skill assessments — delivered through a fast, elegant interface built to keep candidates in flow instead of fighting the tool.
Multiple-choice questions that verify foundational understanding of a domain or tool.
Open-ended or structured questions that probe how a candidate reasons through a technical problem.
Role-specific tasks calibrated to the seniority and scope of the position being hired for.
Question banks tailored to a function — engineering, support, sales, or operations.
Instead of asking a candidate to describe their skills, Skillytal puts them inside a realistic workplace scenario and evaluates how they actually think — decision-making, reasoning, technical understanding, prioritization, and problem solving, all in one response.
Every interview, assessment, and scenario response is scored across the same eight dimensions, then combined into a single, explainable evaluation.
Depth of domain understanding
Structured reasoning under constraints
Clarity and structure of a response
How conclusions are reached
Delivery signals during a response
How closely an answer fits the question
Patterns observed across the session
Environment and identity signals
Where the product architecture supports it, Skillytal runs AI-assisted proctoring directly on the candidate's device — producing signals for human review, not unsupported accusations. Skillytal does not claim to catch every possible integrity risk.
Detects when more than one person appears in frame
Flags smartphones, tablets, and other displays in frame
Identifies potentially relevant reference material in view
Monitors whether the candidate stays visible throughout
Notices sudden angle changes, obstructions, or feed drop-outs
Checks visible mouth movement against detected speech and audio
Reads speaking rate, pauses, and vocal dynamics — not emotion
Notices lighting, background, and setting changes mid-session
These are AI-powered signals designed to identify potential concerns for human review — not automated verdicts, and never a claim to detect emotion, deception, or truthfulness.
Skillytal never claims to catch every AI overlay or every form of external assistance. Rather than relying on a single method, it combines independent signals from across the session into one risk indicator for human review.
Weighs every signal together — no single input determines the outcome.
Every session — interview, assessment, and scenario — rolls up into one structured report, with a question-by-question breakdown behind it.
Sarah demonstrated strong system-design fundamentals and communicated trade-offs clearly under time pressure. Reasoning was consistent across follow-up questions, and no integrity signals were flagged during the session.
Run adaptive interviews, structured assessments, and client-side proctoring in a single, connected evaluation flow.