AI Moderator
Avatar video, voice or text — one AI moderator that runs semi-structured interviews at scale, in the channel that fits your participants.
Try the AI moderator
Talk to it as a video avatar, by voice in your browser, by text chat, or by phone — in 15 languages.
Video call in your browser
Important: This requires microphone and video access.
From human moderator to AI text, voice and video avatar
Four ways to run a semi-structured interview — pick the mode that fits the study, or combine them
Human moderator
Your own moderators run the session. Evidano transcribes and analyses the recordings.
AI text chatbot
Probes in writing. Participants type at their own pace, in private, in the app they already use.
AI voicebot
Listens and follows up by voice. No camera, no typing — just a voice call from the interview link.
AI video avatar
A face-to-face interview with an avatar that sees expressions and reacts in real time.
How the modes compare
Candor, depth of data, engagement, and what only each mode can do
| Human | AI text chatbot | AI voicebot | AI avatar | |
|---|---|---|---|---|
| Best use cases | Complex exploratory work needing human judgment. | Sensitive topics, confidential feedback, private participation. | Storytelling, customer journeys, diary studies, low-literacy groups. | Youth and branded research, visual reactions, long interviews. |
| Candor & comfort | Most social pressure Only 7–19% want a human interviewer next time.1 | Judgment-free 40–50% prefer the AI next time.1 | Most comfortable 55% prefer the AI; 7% a human.1 | Face-to-face feel Visual presence makes the camera feel natural. |
| Data collected | Deep in person only Quality 3.53/5 in person, 1.99/5 by text chat.1 | Deep and concise 2.4× the words of an open-text survey.1 | Richest measured Quality 3.50/5, level with human experts in person.1 | Richest overall Adds expressions, gaze and visible reactions. |
| Engagement | Varies by interviewer Quality varies 19% more than with AI.1 | Engaging 77% wouldn’t swap it for open-text boxes.1 | Preferred way to talk 54% prefer talking; 17% typing.1 | Highest presence Visual presence sustains attention. |
| Unique capability | Human judgment Can challenge assumptions and drop the guide. | Private reflection Reread, pause and rewrite, unseen and unheard. | Speech without visibility Spoken disclosure with no camera. | Visual interaction Reacts to expressions; supports “show me” research and brand mascots. |
Swipe sideways to compare all four modes
Used by
Trusted by end-user companies and leading market research firms
End-user companies
Research companies
Universities & research institutions
Benefits of AI moderator
Why AI moderation goes deeper than surveys and scales where humans cannot — each benefit is tagged with the modes it applies to
Multilingual moderation across 100+ languages and accents
Conducts and understands interviews in over 100 languages, dialects, and accents — spoken or typed.
Consistent moderation across every participant
Asks every participant the same way, with no interviewer drift or fatigue, whichever mode they join through.
No scheduling or interviewer availability constraints
Runs 24/7 on demand, so participants join whenever it suits them — from a link, a message, or a call.
Private, candid disclosure on sensitive topics
People open up more to an AI than to a person. Text is the most anonymous and reflective mode; voice adds spoken candor without a camera.
Probes beyond and navigates the interview guide intelligently
Follows up on interesting answers and adapts the guide in real time, in every mode.
Sees expressions, gaze, and “show me” moments
Reads facial expressions and visible reactions, attaches perception signals to the transcript, and lets participants hold products or screens up to the camera.
Scales rich qualitative data collection affordably
Collects deep qualitative data from many participants at a fraction of the cost of human moderation.
Interviews at the moment that matters
Speaks with participants right after an experience — leaving a store, finishing an appointment, trying a product — capturing reactions while they are fresh and reducing recall bias.
Meets participants in the channels they already use
Runs from a link on any phone or laptop, so taking part fits into the day — no app to install, no desk to sit at. Voice interviews also run as a phone call, WhatsApp call or Telegram call, and text interviews over SMS, WhatsApp, iMessage or Telegram.
Richer stories through natural speech
When people answer by voice instead of typing, graders who don’t know which is which rate the same AI interviews markedly higher (3.6 vs 2.8 out of 5). People share more when they talk, and speech keeps the pauses, emphasis and spontaneous detail that typing edits away.1
Private reflection: pause, reread, rewrite
The only mode where participants can silently reread the question, pause, and rewrite their answer without being heard or watched.
Reaches low-literacy and low-bandwidth participants
A voice interview needs no reading, no camera, and very little data, so hard-to-reach groups can take part on equal terms.
Playful avatars for youth and student research
A unicorn, robot, or friendly peer-like avatar makes interviews feel less formal, encouraging children and students to talk more freely — with avatars matched to age group and study tone.
Embody your brand mascot
The avatar can take the form of a mascot — think Colonel Sanders, Mr. Clean, Flo, Duolingo’s owl, or Mailchimp’s chimp — so branded research feels like the brand.
Expert-level command of highly technical subjects
Briefed on your domain before the interview, it recognizes specialist terminology, workflows, and regulations — and asks informed follow-ups a generalist moderator might miss.
Longitudinal research with continuity
Interviews the same participants over months or years, retaining context from earlier sessions to follow up on past decisions and goals. Diary-style check-ins work especially well by voice and text.
Key Features
Everything you need to design, run, and scale AI-moderated interviews — by avatar video, voice or text
Run mixed methods research in a single survey link, or conduct pure AI-led semi-structured interviews.
Configure each study as a single-link mixed methods experience where participants answer structured survey questions before receiving a targeted 5 to 10 minute AI-moderated probe, or run a full 60 minute semi-structured interview that explores participant experiences, motivations, emotions, and decision-making in greater depth.
Test concepts, images, videos, ads, packaging, and other stimuli in a natural conversation.
Present research stimuli such as product concepts, claims, images, videos, advertisements, packaging, prototypes, or messages, then let the AI moderator ask natural follow-up questions that capture first impressions, emotional reactions, comprehension, appeal, relevance, preferences, and the reasons behind each response.
Customize how the AI moderator probes, speaks, and adapts to each participant.
Set the moderator’s probing depth, tone, language complexity, and conversational style, from light clarification to deeper exploration and from simple, warm language to more technical or domain-specific moderation, so every interview feels natural while collecting the right level of qualitative depth.
Control how flexibly the moderator follows the guide while keeping participants meaningfully on topic.
Choose strict, balanced, or flexible topic control so the moderator can stay closely aligned to your interview guide, allow useful natural detours, or gently steer participants back when they become irrelevant, repetitive, too brief, or move away from the research question.
Embed AI-moderated interviews into your existing recruitment, panel, fieldwork, or digital workflow.
Integrate the interview flow with your panel provider, recruitment process, fieldwork operations, website, app, survey tool, messaging channels, or research platform so participants can move smoothly from invitation to screening to interview without manual coordination.
No complex logic is required because the AI moderator adapts intelligently in real time.
Define your research goals, interview guide, target topics, and moderation preferences, then let the moderator decide when to ask for clarification, examples, reasons, comparisons, emotional reactions, or deeper explanation without requiring you to manually program every branch, skip rule, or follow-up question.
Reach more participants across mobile, laptop, telephone, and low-bandwidth environments.
Let participants join from any compatible mobile or laptop device, enable audio-only mode when a weak connection is detected, or run the interview as a voice call (web link, phone, WhatsApp or Telegram) or a text chat, so the study remains accessible, smooth, and easier to complete even in lower-bandwidth settings.
Improve recognition and delivery with custom dictionaries and pronunciation controls.
Add brand names, technical terms, acronyms, local phrases, participant vocabulary, or pronunciation guidance so the moderator can better understand what participants say and speak key words more naturally during the interview.
Screen, qualify, and route participants before the interview starts.
Add eligibility questions, qualification criteria, consent checks, quotas, and screening rules so only the right participants enter the AI-moderated interview and your final dataset remains relevant, high-quality, and ready for analysis.
Run interviews over SMS, WhatsApp, iMessage, or Telegram.
Send the interview into the messaging app participants already open every day. The AI moderator probes in writing, participants answer at their own pace, and every transcript is ready for analysis in Evidano alongside your avatar interviews.
Interview by phone call, WhatsApp call or Telegram call.
Run the interview as an ordinary phone, WhatsApp or Telegram call. No camera, no typing, and no data-heavy video — the voicebot listens, follows up, and transcribes, which suits storytelling, diary studies, and low-literacy participants.
Evidence: AI vs human interviews
Independent studies find AI-led interviews match human interviewers and go deeper than open-text surveys
Transcript quality score1
Graded 1–5 by sociology PhDs who didn’t know who ran each interview.
Preferred interviewer for next time1
After AI voice interviews (N=338).
Share of active-listening lapses (lower is better)2
Participants could type or speak to the AI (11 interviews).
Words written per respondent1
Same questions (N=461).
Transcript quality score, graded blind1
8 sociology PhDs graded each transcript without knowing who ran it. 1 = worst expert · 3 = average · 5 = best. Whiskers show 95% confidence intervals.
AI voice matched human experts interviewing in person. In text chat, the AI clearly beat human experts: the confidence intervals don’t overlap.
Preferred interviewer for next time1
Share of respondents after each AI interview study
In every study, voice or text, more people chose the AI than a human.
AI text interview vs open-text survey1
RandomizedSame questions · participants randomized to one or the other · N=461Which answer gives a deeper understanding?
Verdicts by sociology PhDs. Whiskers show 95% confidence intervals.
“I can clearly pinpoint my answer”
Statistically significant (p ≈ 0.01)Share of respondents afterwards (201 vs 260). Whiskers show 95% confidence intervals calculated from the reported shares.
People were assigned to each format at random, so the gap comes from the AI interview itself: its follow-up questions helped people work out what they think.
Randomized trial · 40 participants3
AI text chat vs trained human interviewers in text chat · 946 responses
Which interview collected more data?
Share of AI-vs-human interview pairs, calculated from the paper’s Mann–Whitney test (U = 329)
Answer quality, rated 1–5
Trained human interviewers did not do significantly better on any measure.
Participant feedback · 20 participants4
Quoted from the paper’s analysis of participants’ feedback on its AI interview platform
“Many participants emphasized the platform’s quick response times and accurate speech recognition capabilities, which contributed to a smooth interview process.”
“Participants consistently reported lower anxiety levels compared to traditional interviews, citing the absence of immediate human judgment as a key factor. … The ability to pace their responses and focus on content rather than physical presentation …”
“The consistency in question delivery and standardized evaluation approach was frequently mentioned as a positive feature.”
Choose the mode that fits the study
Transcript quality score, spoken vs typed answers1
RandomizedSame AI interviewer; respondents randomly assigned to talk or type. Whiskers show 95% confidence intervals.
Preferred way to talk to an AI interviewer1
After AI voice interviews (N=338)
What participants said
Verbatim feedback from respondents after AI text interviews1
“The AI did a great job, it felt like I was speaking to a real person.”
“The questions were easy to understand and I felt I could be honest without being judged.”
“I felt like I could be more truthful.”
“The response questions actually helped me come up with meaningful answers.”
“The algorithm does not judge me and allows for an in-depth conversation.”
“It is easier, there is no judgment or conflict.”
Sources
- 1.Geiecke, F., & Jaravel, X. (2026). Conversations at Scale: Robust AI-led Interviews. The Review of Economic Studies. https://www.restud.com/conversations-at-scale-robust-ai-led-interviews/
- 2.Wuttke, A., Aßenmacher, M., Klamm, C., Lang, M. M., Würschinger, Q., & Kreuter, F. (2025). AI Conversational Interviewing: Transforming Surveys with LLMs as Adaptive Interviewers. In Proceedings of the 9th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCH-CLfL 2025), pp. 179–204. Albuquerque, NM: Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.latechclfl-1.17
- 3.Gårdhus, T. P., Vitsakis, N., Frederiksen, F. L., Rogers, A., & Carlsen, H. B. (2026). AInterviewer: A Platform for Designing and Conducting AI-led Qualitative Interviews. In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations), pp. 119–127. San Diego, CA: Association for Computational Linguistics. https://doi.org/10.18653/v1/2026.acl-demo.12
- 4.Liu, F., & Yu, S. (2025). Step Further Towards Automated Social Science: An AI-Powered Interview Platform. SSRN Working Paper No. 5120349. https://doi.org/10.2139/ssrn.5120349
Browse avatars, languages & accents
Pick from our full library of AI avatars, choose from 30+ interview languages, and preview the accents available for each — the same options you get when creating your own study.
Real research, real depth
How universities and global brands use the AI survey / interview to uncover the reasoning behind the data — at scale.