Interview Insight.
Survey Scale.

An AI-moderated interview is a qualitative research session conducted by artificial intelligence within WhatsApp. Unlike static chatbots that follow fixed scripts, AI interviewers use generative language models to understand participant responses in real-time and ask intelligent, adaptive follow-up questions (probes) to explore deeper motivations, just like human researchers do.

Yes. Participants can respond via text, voice notes, or video in WhatsApp AI interviews. When participants send voice notes, the system automatically transcribes the audio, analyzes the content, and generates relevant follow-up questions based on what was said. This creates a seamless, voice-first conversational research experience.

While human moderation provides deep psychological nuance, it is slow and expensive to scale. AI interviewing allows researchers to conduct hundreds or thousands of in-depth interviews simultaneously—a scale impossible for human moderators. AI interviews bridge the gap between the broad reach of surveys and the qualitative depth of focus groups, though they work best when supplementing rather than replacing human research expertise.

Yes. AI interview systems can typically conduct conversations in dozens of languages, including local dialects (such as Afrikaans, French, Portuguese, Japanese and Arabic). The systems automatically translate transcripts back into the researcher's preferred language for analysis, breaking down language barriers in global research projects.

AI-moderated interviews are significantly more cost-effective than traditional qualitative methods. Traditional qualitative research involves high recruitment, facility, incentive, and moderator fees per session. AI interviews can reduce these costs by up to 70%, allowing researchers to conduct qualitative projects at quantitative sample sizes and budgets.

Traditional surveys force participants into pre-defined answer choices (A, B, or C). AI interviews allow open-ended exploration where the system can identify when participants give short or vague answers and gently probe for more detail. This captures rich, nuanced insights that standard multiple-choice surveys would miss, while still maintaining the scale advantages of automated data collection.

Yes. Researchers set the "discussion guide" or core research objectives before launching AI interviews. Most platforms offer hybrid models where specific structured questions are mandatory, while allowing the AI to probe for depth on open-ended responses. Researchers can also set "guardrails" to ensure the AI stays focused on relevant topics.

Yazi uses an automated classification systems that categorize each question by type and each participant answer using tailored category sets. To prevent AI hallucination, the systems typically use number-based category selection rather than generating new text labels, ensuring consistent classification across large datasets. The platforms then generate executive summaries and identify recurring themes automatically, allowing researchers to move from hundreds of transcripts to actionable insights in hours rather than weeks of manual coding.