산업별

Evaluates how well a team communicates, makes decisions, shares workload, and supports its members — straight from the people doing the work. Built for managers and HR running regular team health checks, with an AI follow-up that digs into the real story behind whatever obstacle or low score members flagged, not just the number they gave it.

A proactive check-in that surfaces why current employees stay, what's quietly pushing them toward the exit, and which factors actually drive retention versus which just feel important. Built for HR and people managers running regular stay interviews. The AI follow-up interview digs into the real story behind each person's retention risk score before it turns into a resignation.

Explores how freelancers and independent contractors actually handle self-employment tax — quarterly payments, deductions, tools, and confidence gaps — with an AI follow-up that digs into the moment their tax bill or process went sideways. Built for tax software makers, accounting firms, and platforms serving the self-employed.

면접관이 스크리닝, 패널, 또는 온사이트 라운드 직후에 지원자를 평가할 수 있도록 구성된 스코어카드입니다 — 핵심 역량, 두드러진 강점, 채용 추천을 다룹니다. AI 후속 인터뷰가 경계선 점수 뒤의 근거를 파고들어, 채용 위원회가 단순한 숫자가 아닌 실제 증거를 확보할 수 있도록 돕습니다.

A structured intake for auditor candidates that captures experience level, certifications, technical proficiency, and role priorities, then uses an AI follow-up interview to probe a real audit challenge the candidate has handled. Built for audit firm recruiters and hiring managers who need comparable, behavior-based screening data before a live interview.

Measures how well a supervisor delivers feedback, availability, psychological safety, and case guidance to the people they supervise — built for healthcare, social work, counseling, and training programs. An AI follow-up interview reconstructs a specific recent supervision moment behind the overall rating, surfacing what actually helped or hindered instead of vague satisfaction talk.

Measures how prone employees are to feeling bored or understimulated at work, using a trait-style statement battery, situational triggers, and coping responses. Built for HR, L&D, and people-analytics teams. An AI follow-up interview reconstructs a real recent boring moment to separate personality-driven boredom proneness from fixable role-design problems.

Measures how people actually experience dating apps and sites — match quality, trust, safety, and what drives satisfaction — for dating product teams and researchers. An AI follow-up interview reconstructs a real recent match or date instead of relying on vague satisfaction ratings.

Assesses how much sleep loss is affecting your workforce's alertness, mood, and safety on the job — built for HR, EHS, and shift-operations teams. An AI follow-up interview digs into the real story behind a recent fatigue-related close call or bad day, surfacing root causes that a checklist alone would miss.

Captures direct reports' candid ratings of their manager's communication, feedback, recognition, and follow-through, plus a best-worst trade-off on which leadership qualities most need development. The AI follow-up interview digs into the concrete story behind the lowest-rated behavior instead of settling for a number.

Explores how people actually use social networking platforms — which ones, how much, why, and how it affects their day-to-day wellbeing. Includes a best-worst trade-off on core motivations and a feature-priority ranking, plus an AI follow-up that reconstructs a specific recent moment the respondent almost quit or actually quit a platform, and what changed their mind.

Collects height, weight, and body-fit feedback from employees who wear company-issued uniforms, workwear, or personal protective equipment (PPE). Built for safety, operations, and HR teams sizing programs across a workforce, with an AI follow-up that digs into where standard sizing breaks down and whether poor fit creates safety or comfort risks on the job.

A structured manager assessment of how a new hire is performing during their probationary period, covering core competencies, training support, and readiness for confirmed employment. An AI follow-up interview probes the concrete incidents and evidence behind the manager's recommendation rather than just the rating, producing feedback the employee can actually act on.

Gathers employee ratings of senior leadership on vision, decision-making, transparency, and accountability, plus behavioral data on how often leaders are visible day-to-day. An AI follow-up interview digs into the specific decision or moment that most shaped each person's confidence — surfacing concrete evidence behind the scores for HR and the executive team.

Measures how often employees experience or witness gender-based discrimination — in pay, promotion, meetings, and everyday treatment — and how safe they feel speaking up. An AI follow-up interview reconstructs a specific incident in the respondent's own words, revealing what actually happened and what response would have felt fair, for HR and DEI teams benchmarking climate and prioritizing fixes.

Measures whether employees believe the organization genuinely cares about their satisfaction and wellbeing, based on behavioral signals like manager check-ins and follow-through on feedback rather than stated policy. An AI follow-up reconstructs a specific recent moment behind each respondent's score, surfacing concrete gaps between what leadership says and what employees actually experience.

A recurring pulse that tracks overall happiness and satisfaction across work, relationships, health, and growth month over month, with an AI follow-up that digs into whichever area is driving the score up or down. Built for HR and people teams running a lightweight monthly wellbeing cadence. Takes about 4 minutes.

Measures where people stand on the death penalty — overall support, which crimes they think warrant it, and how they weigh deterrence, cost, fairness, and wrongful-conviction risk — with an AI follow-up that surfaces the reasoning and tensions behind their stance. Built for policy researchers, advocacy groups, and pollsters.

Assesses how news consumers judge the accountability practices of the outlets they follow — corrections, sourcing, transparency about ownership and conflicts of interest — and prioritizes which practices matter most to trust. An AI follow-up interview reconstructs a specific incident where trust in a news source was gained or lost. Built for newsrooms, media watchdogs, and researchers studying press credibility.

Assesses how consistently frontline staff (food service, healthcare, childcare, hospitality) follow personal hygiene protocols, what gets in the way, and where facilities or training fall short. An AI follow-up interview reconstructs a real recent moment of non-compliance instead of relying on self-reported good intentions, giving managers concrete, actionable gaps to fix.