ReDem by Rep Data

ReDem®: AI-Powered Quality Assurance for Survey Data ____________________________ English Short description ReDem® is a leading ResTech (Research Technology) company specializing in AI-based SaaS solutions for survey data quality assurance. Our goal is to help the insights industry make quality control and data cleaning more efficient and standardized. ReDem is a data quality assurance platform for online surveys. It runs AI-powered checks in-field or post-field to detect inattentive, inconsistent, or fraudulent interviews (including bots and click farms). It enables real-time cleaning and live quota management, and generates a transparent quality score and report for research teams. Long description With AI tools in everyone’s hands, survey data integrity is under growing pressure. Fraud is getting smarter and therefore harder to catch, making manual data cleaning not only time-consuming but also increasingly ineffective. ReDem® is the data quality solution used by market researchers worldwide to review and clean survey data in real time. ReDem automatically identifies, among other things, open-ended responses that are off-topic, duplicated, or AI-generated, detects contradictory or inconsistent answers, and flags suspicious typing and input behavior such as copy-and-paste patterns or unnatural, bot-like typing activity. The result: faster analysis, reliable insights, and consistently high data quality. Very long description With AI tools in everyone’s hands, survey data integrity is under growing pressure. Fraud is getting smarter and therefore harder to catch, making manual data cleaning not only time-consuming, especially when projects run at scale across multiple markets and suppliers, but also increasingly ineffective. ReDem® is a data quality assurance platform for online surveys that helps research teams identify and remove low-quality and fraudulent interviews both during fieldwork and post-field. It combines multiple quality signals into a single, transparent framework, so teams can make faster, more consistent cleaning decisions and confidently explain those decisions to internal stakeholders and end-clients. How ReDem evaluates data quality (key checks) ReDem runs a 360-degree set of checks across the entire interview. Each check is designed to detect a specific class of quality risk; together, they provide a robust view of whether an interview is trustworthy. Open-end quality checks (Open-Ended Score / OES): ReDem reviews open-ended responses for patterns that typically indicate low engagement or fraudulent completion, for example, off-topic or generic answers, duplication across answers and across respondents, AI-generated text in open-ends, nonsensical text, and more. Coherence and consistency checks (Coherence Score / CHS): The Coherence Score is an AI-powered check that assesses the logical consistency of a respondent’s answers across the entire interview. It also flags subtle contradictions that are hard to catch manually at scale, such as location vs. transport use, household details vs. purchase claims, or inconsistencies across related questions. No predefined rules or manual setup are required; the model detects these contradictions automatically. Timing and speeding checks (Time Score / TS): ReDem assesses interview duration and question-/section-level timing patterns to identify respondents who move implausibly fast, appear to skim, or show completion behavior inconsistent with genuine participation. Rather than relying on a fixed threshold, timing is interpreted dynamically relative to other respondents in the same survey. Grid and patterning checks (Grid-Question Score / GQS): For batteries and grids, ReDem detects straightlining, partial straightlining, zig-zagging, and other patterns and low-engagement behaviors in grids. Behavioral and input-signal checks (Behavioral Analytics Score / BAS): ReDem’s Behavioral Analytics Score analyzes keystroke patterns while respondents type open-ended answers. It flags copy-paste activity and other bot-like typing behavior, helping detect AI-driven completion where the text may look convincing but the input patterns are not consistent with natural human typing. In-field protection and post-field assurance ReDem supports both real-time and post-field workflows: In-field (real time): ReDem can be used via an API integration with your survey platform, returning quality scores while the survey is live. This enables early identification of low-quality interviews so they don’t count toward completes or distort quotas, reducing re-recruitment and avoiding delays from late-stage quality surprises. Post-field: ReDem can also be used by uploading the dataset to the platform and downloading the assessed file with all quality scores and flags applied. All checks are available post-field except BAS. Transparent scoring and defensible decisions All check results are consolidated into the ReDem® Score (R-Score), an overall indicator of interview quality that makes it easy to prioritize review and apply consistent decisioning across studies. Importantly, ReDem is built for defensibility: teams can review interview-level drivers behind flags, calibrate cleaning settings to match study context and client requirements, and generate a transparent quality report documenting the checks applied and the rationale for exclusions. Ultimately, ReDem helps research teams spend less time on manual cleaning and more time on insight, while strengthening trust in the data through consistent, scalable, and auditable quality assurance.