The full journey a candidate and a hiring team take through Skillytal — how a single assessment session becomes a structured, reviewable report.
Nothing here is a black box. Each step below feeds directly into the next.
Send a personalized assessment link
Identity and device checks complete
Conversational or structured format
Audio, vision, and behavior in real time
Every answer scored across dimensions
A structured report is compiled
Review a summary, not raw transcripts
A recruiter sends a scoped, time-bound link tied to a specific role and candidate. When the candidate opens it, Skillytal runs identity and device checks before any question is asked — confirming camera and microphone access, checking the environment, and preparing the session so the interview itself starts clean.
From there, the AI selects a format: a live conversational interview, a structured technical set, or a mix of both, depending on how the role was configured.
As the candidate speaks or types, Skillytal is already working — the AI is choosing adaptive follow-up questions based on what was just said, while audio, vision, and behavioral signals are captured in parallel. Nothing here waits for the session to end.
Every response is scored the moment it's complete, across technical depth, communication, and problem-solving, then rolled into the growing evaluation for that candidate.
Once the assessment ends, the AI evaluation engine combines every scored response and every observed signal into a single candidate report — technical skills, communication, problem-solving, behavioral signals, and integrity signals, all in one place.
The report is generated automatically, with no manual scoring step required from the recruiter.
Instead of reading a full transcript, the recruiter opens a structured summary: an overall score, a breakdown by dimension, an AI-written summary of strengths and gaps, and any integrity signals worth a closer look.
That's the shift — from hours of manual review per candidate to minutes of structured comparison across all of them.
The same nine-stage pipeline runs behind every assessment, regardless of format.
The candidate's session opens after identity and device checks pass.
The AI selects or adapts each question based on role and prior answers.
Spoken, written, or selected responses are captured the moment they're given.
Pace, pauses, and speech consistency are extracted from the response.
Camera-based observations are processed on-device where supported.
Interaction and timing patterns are tracked across the full session.
Each answer is scored per question against the role's rubric.
All scored dimensions and signals are weighed together, not in isolation.
Everything above compiles into one report built for a hiring decision.
A second look at how one response gets read, scored, and turned into signal — this time on a different question.
Simulated demonstration — not a live model response
A simulated demonstration — pick an answer and watch the evaluation flow run.
The report isn't the end of the process — it's what makes the next step faster. Here's how it fits into a day-to-day hiring workflow.
Every candidate is scored on the same dimensions, so shortlisting is a comparison, not a re-read
A structured summary replaces reading a full transcript question by question
The same rubric is applied to every candidate for a role, reducing reviewer-to-reviewer variance
Integrity and skill gaps surface in the report itself, not after a candidate has already advanced
Send a real assessment link and watch a candidate move through the same flow described above.