Understand the risk
AI survey integrity guides
Survey fraud detection and data quality in the AI age.
Evidence-based guidance for detecting AI-generated survey responses, survey bots, AI agents, and other suspicious activity without mistaking one signal for proof.
Improve survey data quality with layered controls, behavioral evidence, response checks, and human review. These guides explain how survey fraud detection works, what each signal can support, and where its limits remain.
01
Understand the risk
Understand the risk
AI agents, bots, and AI-assisted people: what is the difference?
Bots, AI agents, fraudulent participants, and AI-assisted people are not interchangeable. They use different paths, create different evidence, and require different responses; a control designed for a simple script may say very little about a person who passes screening and later uses an AI assistant.Read this survey integrity guide02
Build layered protection
Build layered protection
How to protect online forms and surveys from AI bots
Protect forms and surveys with several independent layers rather than one “bot blocker.” Reduce unnecessary exposure, use native platform controls, design the instrument carefully, collect relevant technical and behavioral evidence, and define a review process before submissions arrive.Read this survey integrity guideBuild layered protection
Why CAPTCHA alone is not enough against AI agents
CAPTCHA remains a useful entry control, but it answers a narrow question at one moment in the session. It cannot establish who completes the rest of a form, whether a response is unique, or whether a human hands the task to an AI after the challenge.Read this survey integrity guideBuild layered protection
How to protect LimeSurvey surveys from bots and AI agents
Protect a LimeSurvey survey by starting with its native participant, token, CAPTCHA, cookie, and access settings, then add monitoring and post-submission review. For stronger survey-specific evidence, Ramon can add behavioral compatibility without sending survey answers to its scoring model.Read this survey integrity guide03
Assess what gets through
Assess what gets through
How to detect AI-generated survey responses
Detect AI-generated survey responses by separating AI-written text, AI-assisted people, scripted bots, and autonomous AI agents, then combining content, behavioral, session, recruitment, and dataset evidence. No single score proves who or what produced a response.Read this survey integrity guideBehavioral survey fraud detection
Add a Human Score after the survey.
Ramon adds behavioral evidence to survey fraud detection by turning completed online survey interactions into a Human Score. It supports review; it does not prove identity or make an automatic fraud decision.