Research

A post-experience research survey evaluating the effectiveness of AI interview moderators across demographic groups. Measures overall experience quality, perceived empathy and understanding, cultural sensitivity, accessibility, and direct comparisons with human moderators. Designed to detect demographic moderation effects.

Measures how safe, fair, and supported people feel in their day-to-day work — trust in leadership, psychological safety, workload fairness, and manager impact — for HR and people teams tracking team health between engagement cycles. An AI follow-up reconstructs the specific moment behind each person's rating instead of settling for a number on a dashboard.

Segments financial app users by usage behavior, feature priorities, trust levels, and demographics to build data-driven personas and inform product strategy.

This survey explores researcher experiences with reproducibility, transparency, and data quality in AI-moderated research. It serves as a replication study template to understand current practices, identify barriers, and assess the role of platform transparency in enabling reproducible AI-moderated studies.

A meta-research coding instrument for researchers to systematically evaluate and compare data quality from AI-moderated interviews versus traditional qualitative methods. Designed for repeated use across multiple data sets. Estimated completion time: 12-15 minutes per data set evaluated.