Survey fraud today ranges from bots and device spoofing to inattentive, low-effort respondents - yet most tools protect only the entry point or the final dataset. This session reviews the data-quality landscape to show what current systems handle well and where gaps remain. We then demonstrate a multi-layer framework, implemented directly within Sawtooth, that uses real-time validation, behavioral signals, AI-led open-end quality checks, and respondent-level scoring to monitor integrity throughout the survey. The takeaway: a practical, replicable way to bring continuous data-quality protection into your Sawtooth studies - turning every complete into cleaner, more dependable insight.
