CQAR Guide

How CQAR Works

A short tour of the product — what each layer does, how grades are computed, and what your hiring team sees.

Step 01

One platform, two assessment layers

CQAR combines structured screening (CQ) with adaptive AI voice interviews (AR). You decide which mix fits each role.

CQ — Candidate Quality screening. Fixed voice questions scored against the role's rubric. Built to filter at scale.
AR — Adaptive Recording interview. Dynamic voice interview that follows up on vague answers and reads behavioural signals.
Per role, you pick CQ only, AR only, or both — the pipeline columns adapt to match.

Step 02

Kanban columns shift based on the role's product type so the team only sees stages that matter.

AR only: Applied → Interview → Offer → Hired.
CQ only: Applied → Screening → Assessment → Offer → Hired.
Both: Applied → Screening → Assessment → Interview → Offer → Hired.
System-driven stages fill from candidate actions. HR-driven stages advance by drag-and-drop.

Step 03

The AI listens, transcribes, and picks the next question based on what the candidate just said.

live interview session

"Walk me through how you'd debug a slow database query at 3 a.m. on call."

Transcribing ·Pace 64 wpm ·Empathy 78% ·Clarity 82%

Follow-up queued: "You mentioned indexing first — when wouldn't that be the right first move?"

Each turn updates pace, clarity, sentiment, and confidence scores.
Vague or surface-level answers trigger probing follow-ups.
Audio is deleted as soon as the session ends — the candidate receives an email confirming removal.

Step 04

Every candidate gets a composite grade A+ through D, with X reserved for incomplete sessions.

A+ / A — Outstanding or excellent fit across all evaluated dimensions.
B / C — Decent or adequate fit with notable gaps.
D — Below standard for key criteria.
X — Interview not completed or insufficient data.
Each grade is backed by Technical Fit, Soft Skills, and Resume Match sub-scores, plus six soft-skill trait categories.

Step 05

Shortlist two or more candidates and CQAR overlays their per-metric scores so the call is data-driven.

Shift-click candidate cards in the pipeline to add them to the shortlist.
Toggle between Table view (full per-row breakdown) and Radar view (overlay chart).
The strongest value in each row is highlighted with a star.

Step 06

CQAR is designed for jurisdictions that regulate AI-driven hiring — disclosure, consent, and audit logs are first-class.

NYC Local Law 144 — informed-participation screen before any candidate assessment, with the acceptance logged.
GDPR-aligned retention — audio is deleted as soon as the session ends; other assessment data is purged after the role's configured window (14 days by default).
No PII in AI prompts — identifying fields are stripped before the model evaluates a response.
Audit trail — every stage transition, score event, and consent action is logged in the pipeline_events table and exposed to HR.

CQAR augments your judgment with evidence. The human always has the final word.

Ready to start? See the Onboarding Guide for first-time setup or the Recruiter How-To for everyday tasks.