UX researchers, PMs, and founders use Eliciteer to run dozens of in-depth user interviews in parallel. Brief the AI, share a link, and get structured qualitative insights at a fraction of the cost of traditional research.
72%
Cost reduction vs traditional research
100s
Parallel user interviews
$150+
Avoided per recruited interview
0
Calendars to coordinate
AI user research uses an AI agent to conduct qualitative user interviews on behalf of your team. Instead of scheduling 30-minute calls with each participant, you brief the AI on what you need to learn — pain points, jobs-to-be-done, feature reactions, willingness to pay — and it runs the conversations asynchronously, in parallel, with as many users as you need.
The AI behaves like a trained researcher: it listens to each answer, asks follow-up questions when something is vague or interesting, and pivots when an unexpected theme surfaces. The output is structured, themed, and immediately actionable — not 40 hours of raw transcripts to code by hand.
Studies show optimized online qualitative research can deliver up to 72% cost savings while reaching dramatically more participants. Eliciteer is built specifically for this workflow.
From research question to structured insights, in three steps.
Describe what you want to learn, your target user, and any hypotheses. Eliciteer plans the interview structure for you.
Send the unique link to your panel, customers, or recruits. Each person interviews on their own schedule.
Each interview is auto-summarized. Spot themes, anti-patterns, and quotes across the cohort in minutes, not weeks.
Talk to 50 users this week, not next quarter. Each gets a personalized AI interview with smart follow-ups.
Skip recruiting overhead, moderator hours, and transcription. Spend the savings on more rounds of research.
The AI probes vague answers and pivots on interesting threads — so you get qualitative depth at quantitative scale.
No more 'find a time that works for both of us'. Users respond when it suits them, from any device.
Every transcript is summarized into the schema you care about: pain points, JTBD, willingness to pay, quotes.
Pipe results to Notion, Dovetail, n8n, or any webhook target. Stop copy-pasting interview notes.
The same depth, with none of the calendar pain — and a fraction of the cost.
Anywhere you'd schedule a 30-minute user call.
Talk to 30 target users in a week to surface pain points, jobs-to-be-done, and unmet needs.
Validate a concept, pricing, or messaging with structured pros, cons, and willingness-to-pay signals.
Run async usability debriefs after a prototype test or feature launch. Capture nuance the survey misses.
Reach every churned customer, not just the few who reply. Get structured reasons and counter-offers.
Run weekly async interviews with your beta cohort. Spot regressions and delight moments without standing meetings.
Interview busy executives across time zones. They reply when they can; you get structured insight back.
AI user research uses an AI agent to conduct in-depth qualitative user interviews on your behalf. You brief the AI on your research goals, share a link with users, and the AI runs the conversations asynchronously — asking smart follow-ups and capturing nuance like a trained moderator would.
AI user research complements rather than fully replaces traditional research. For exploratory, generative, and large-N interviews, AI delivers comparable depth at a fraction of the cost. For sensitive, ethnographic, or highly contextual research, human moderators are still ideal — and many teams use AI to scale the discovery rounds and reserve human time for the deepest sessions.
Surveys collect what respondents choose to type. An AI user research interview asks follow-up questions when answers are vague, probes on themes that matter, and pivots when something unexpected surfaces. The output reads like a researcher's notes, not a CSV of free-text fields.
There is no practical limit. Teams routinely run 50-500 AI user interviews in parallel. Pricing is plan-based, not per-interview, so scale doesn't blow up your research budget.
Every interview is auto-summarized into the schema you define in your briefing — for example, pain points, jobs-to-be-done, willingness to pay, key quotes. You can also pipe results to Notion, Dovetail, n8n, or any webhook target for downstream analysis.
Yes. All interview data is encrypted in transit and at rest, and we do not use your data to train AI models. We recommend always disclosing to participants that an AI is conducting the interview — Eliciteer makes this transparent by default.
Run your next round of user research async, in parallel, with structured insights ready when you wake up.
Start Your Research