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Built on the practice of Deal , where strategy meets user experience

AI-powered user research,
for every decision,
every day.

Before 6 weeks
With RapiQ 0 hours
1
Design
2
Fieldwork
3
Analysis
4
Report

AI drafting the study outline

AI
What would you like this study to find out?
Let AI decide
U
AI is filling this in
🌐

Audience

✨ AI

Employees at companies with remote-work policies

📄

Background

✨ AI

Needs differ widely by job function

💡

Hypothesis

Talking to AI…

🎯

Objective

Talking to AI…

📊

Method

Talking to AI…

Parallel Interview

87/100

AI Interviewer · asking

“When do you feel most focused?”

6 people answering at once
A
A.M

“Waiting to answer”

M
M.K

“Early mornings on my work-from-home days…”

T
T.N

“Waiting to answer”

K
K.S

“Reviews reward whoever is most visible…”

Y
Y.H

“Waiting to answer”

R
R.O

“Waiting to answer”

Piped straight into analysis
#focus-time#too-many-meetings#reviews
Findings extracted3 items

Work-setup needs conflict fundamentally across roles

UrgentAnswers the objective

Engineering wants fully remote, sales and managers want hybrid, HR wants a return to the office.

💡4 supporting quotes

“For engineering roles like mine, I want fully remote to stay.”

Insight report
5 slides
Title
Title
1
Conclusion
2
Context
3
Method
4
Findings
5
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Why we built it

Why user research
has always been
a luxury.

Everyone already agrees that you should ask your users. And yet a single study still takes one to two months and costs hundreds of thousands of yen. Writing good questions and probing well takes real expertise — and outsourcing it means several meetings just to agree on the brief.

Wall 01

Time

Design, fieldwork, analysis, reporting: one to two months. When the decision is due this week, that is too late.

Wall 02

Cost

Hundreds of thousands of yen per study. Every hypothesis you want to test spends budget you may not have.

Wall 03

Expertise

Question design, probing, analysis, reporting. Four different crafts — never work that just anyone could pick up.

Wall 04

Buy-in

A study that expensive needs sign-off before it can start. “Let us just ask” was never actually an option.

So a valley opened up between what teams should do and what they can actually do — and most of the questions quietly sank into the “later” folder.

A New Beginning

A new kind of user research,
built with AI.

Thirty user voices are already on the table before the decision meeting starts. Research stops being a special project and becomes part of the working week. RapiQ is how “we should ask” becomes “we already did”.

How RapiQ AI works · in 30 seconds

One AI, running
all four stages.

Classic research is a straight pipeline — design → fieldwork → analysis → reporting — handed between different people using different tools, over six weeks. RapiQ runs all four on a single AI. One platform, where each output is directly the next input.

AI

seamless

01 Design 30 min
02 Fieldwork 1–3 days
03 Analysis same day
04 Report same day
01

Remove the handoffs. One platform, where each output feeds directly into the next stage.

02

Put the expert’s craft in everyone’s hands. AI distributes the tacit knowledge of design, probing and analysis.

03

Move the moment results arrive. Insight is in your hands from the second the responses land.

See what each stage produces

Results

The study runs overnight.
5 seconds later, the results are yours.

AI runs fieldwork and analysis through the night. By morning, the summary, the key findings, the representative personas and the recommended next steps are all waiting on a single screen.

  • Study summary — Overall patterns and response distribution on one page.
  • Key findings — Extracted by AI, ranked by tag and importance.
  • Representative personas — Generated automatically from response clusters.
  • Next actions — Concrete moves to take, proposed for you.

AI talks to 100 people
in parallel, on your behalf.

Working from the scenario you designed, an AI moderator probes one-on-one — running 100 conversations at once and building a structured transcript from every one of them.

  • Structured transcripts — Questions, answers and tags, all recorded automatically.
  • Automatic tagging — AI surfaces the telling quotes in real time.
  • 100 in parallel — A large qualitative study, finished in a day.
  • Contextual probing — AI keeps asking “why?” where it matters.

A working outline in
5 minutes of conversation with AI.

Describe the background and the goal in a sentence. AI generates the research questions, the hypotheses and the survey items — assembling a professional researcher’s design as you talk.

  • Requirements, structured — Plain language → hypotheses → questions.
  • Scale suggestions — AI picks numeric, ordinal or open-ended.
  • Research questions — AI checks for the gaps you would have missed.
  • Design summary — Ready to share internally as-is.

An AI-generated report
you can circulate as it is.

Key findings, personas and recommended actions are laid out into slides automatically. Export to PDF or PPTX and share it with stakeholders on the spot.

  • Slides, generated — A structured 10–12 slide report.
  • PPTX / PDF export — In a format you can keep editing.
  • Evidence with quotes — One click back to the tagged quote.
  • Action proposals — AI adds the expected impact of each.
www.rapiq.jp/projects/24/analysis
Results
AI interviews
Study design
Reports
6 AI Capabilities

Any one of them is
a reason to use it.

From framing the question to proposing the next move, AI runs through all six. Any single one changes how you research tomorrow. Click a card to look inside.

01 · Design

Goal

Find out why existing users churn

RQ

At which moment do they decide to leave?

Hypothesis

Week-two notification frequency is the trigger

12 questions 4 probe rules

AI structures the design

One line of intent, and the research questions, hypotheses and items are all there.

02 · Interview
“When did it start feeling hard to use?”

100 conversations, in parallel

One-on-one probing, run all at once. Recording and tagging included.

03 · Finding

Analysis summary

A complicated application flow is holding usage down.

82%
64%
47%
⚠ Important NEW

Findings surface on their own

AI pulls out what matters, what is new and what contradicts — quote attached.

04 · Persona
Portrait of a representative persona
Misaki Sato 38 · HR manager

GOALS

Raise uptake of the policy and lift employee satisfaction

PAINS

A convoluted request flow; no way to hear the floor

Personas, assembled for you

Whole people with goals and pains, generated as a set from real clusters.

05 · Report

The report lands finished

Findings through to actions, laid out automatically. Share as PPTX or PDF.

06 · Action

Stop the Tuesday morning notification

Redesign step 3 of onboarding

Embed a survey in the cancellation flow

AI proposes the next move

“So what do we do?” answered with specific actions. Findings become motion.

    Give your team the
    everyday of user research.

    Tell us about the research question you are stuck on.

    30 minutes
    No expertise needed
    Reply within 1 business day