Employee & HR

Measures the gap between the values a company says it holds and the values employees actually experience in day-to-day decisions, priorities, and leadership behavior. Built for HR and leadership teams auditing culture health, with an AI follow-up that reconstructs a real recent moment where a decision either honored or contradicted a stated value.

Measures employee interest, schedule preferences, acceptable trade-offs, and operational concerns related to adopting a compressed or reduced workweek. Designed for HR and leadership teams evaluating workweek policy changes.

Measures how smoothly new clients moved from signed contract to real value — covering communication, clarity of next steps, and time-to-value — with an AI follow-up that reconstructs exactly where friction happened instead of relying on a single satisfaction number.

Measures employee Net Promoter Score on a standard 0–10 scale and identifies the workplace factors driving or hindering advocacy, enabling targeted improvements to employer brand, engagement, and retention.

Measures employees' access to growth opportunities, mentorship quality, career path clarity, and internal mobility confidence to inform talent development strategy and retention initiatives.

Measures employee perceptions of desk/hot-desking system usability, allocation fairness, and access barriers over a 4-week lookback period to guide UX and policy improvements.

Measures employee comfort with workplace monitoring practices, evaluates policy transparency, and identifies trust gaps to guide privacy, consent, and communication improvements.

A structured self-assessment covering goal achievement, manager support, and growth priorities for the current review period, for use in performance reviews or pulse check-ins. An AI follow-up interview reconstructs the specific achievement or obstacle behind the respondent's self-rating instead of leaving it as an abstract number.

A monthly pulse survey measuring hospitality employees' perceptions of role clarity, coaching quality, recognition, and workplace support over the past 30 days. Designed for property-level or multi-unit tracking with built-in segmentation by role, tenure, and shift.

Measures how included, fairly treated, and heard employees feel across backgrounds, and prioritizes where DEI investment would have the most impact. An AI follow-up interview digs into specific belonging or fairness experiences behind the scores instead of leaving them as abstract ratings.

A supervisor-facing evaluation of a call center agent's call quality, adherence, and soft skills, paired with a best-worst training-priority ranking and an AI follow-up interview that reconstructs a specific recent call to explain the reasoning behind the ratings. Built for team leads and quality analysts running periodic performance reviews.

Measures employee participation patterns, motivational drivers, and barriers to workplace wellness engagement. Designed for HR and wellness teams seeking actionable data to improve program design, communication, and uptake.

Measures how employees actually feel about the branded merchandise they receive — quality, frequency of use, and which items feel worth keeping — plus a best-worst trade-off to prioritize future swag spend. An AI follow-up interview digs into the story behind their most memorable item to surface what actually makes swag feel meaningful versus wasted.

A voice AI exit interview departing employees can take privately, on their own time. The interviewer covers reasons for leaving, manager and culture experience, and what would have changed their mind — probing gently where a form gets one-word answers. Structured questions capture the benchmarkable basics.

Measures how employees actually experience the meetings on their calendar — frequency, agenda discipline, time well spent, and what they'd fix first — with an AI follow-up that reconstructs a specific meeting that felt like a waste of time and what would have made it worth attending.

Gathers structured multi-rater feedback—from managers, peers, direct reports, and self—on an employee's core competencies and overall effectiveness. An AI follow-up interview digs into the concrete behavioral examples behind the ratings, turning vague impressions into specific, actionable evidence for development conversations.

Measures how attuned staff feel to patients' needs and how safe they feel speaking up about care or safety concerns, surfacing barriers to raising issues and signs of moral distress. Built for healthcare and care-setting HR and quality teams, with an AI follow-up that reconstructs what actually happened the last time an employee flagged a concern.

Identifies where new users encounter friction during signup, setup, and first use, enabling product teams to diagnose activation blockers and optimize time-to-value.

A CNBC|SurveyMonkey-style workforce pulse that tracks how happy, secure, and engaged employees feel right now — covering pay fairness, workload, leadership trust, and flight risk. An AI follow-up interview digs into the story behind low happiness or job-security scores so HR and leadership see the real drivers, not just the number.

Evaluates the clarity, timing, and helpfulness of in-product onboarding guidance (tooltips, walkthroughs, checklists) to identify friction points and improve activation for new users.