AI-assisted follow-ups
Follow an answer with a relevant question using your research goal and interviewer instructions. Explore an expectation, a workaround, or a recent decision without scripting every branch.
Explore AI-assisted follow-upsThe UserTold feature tour
AI-assisted interviews, recordings you can revisit, and evidence you can inspect. Keep what users said and did connected to the work you choose to build.
01 / Listen in context
Talk with people while the experience is still fresh. Give the interviewer a research goal, then let the conversation follow what the participant actually says and does.
“I went back to account settings. That’s where I expected to find the plan.”
“What made account settings feel like the right place to look?”
Your research goal guides the conversation. The participant’s answer gives the next question its context.
Follow an answer with a relevant question using your research goal and interviewer instructions. Explore an expectation, a workaround, or a recent decision without scripting every branch.
Explore AI-assisted follow-upsLet a participant work through a task in silence. Enable pre-debrief analysis for the next Talk step to ask about recent speech, behavior, and page changes.
Explore Observe, then debriefCombine Talk, silent Observe, and scripted Speak steps. Set the goal, instructions, and pacing for the interview you need to run.
Explore A flow you can shapeAdd product facts and terminology. When more detail is needed, connect an existing read-only knowledge endpoint and enable it for the relevant Talk steps.
Explore Product context for the interviewer02 / Return to the source
A Finding should take you back to something you can inspect. Review the recording alongside the transcript and the product events that give the conversation context.
The participant opens account settings, returns to the previous page, then opens account settings again.
“I didn’t know the plan belonged to the workspace.”
Account and workspace ownership may be unclear. Review the recording and other interviews before deciding where plan controls should live.
Replay the participant’s shared screen alongside their voice. Screen capture is available in supported desktop browsers when the participant grants permission.
Explore Recorded screen reviewMove between speech, navigation, interactions, and evidence moments. Seek into playback to understand what happened before and after a quote.
Explore Transcript and timelineInspect direct quotes, observed facts, behavioral reconstruction, and the claim they support. Page context, preceding actions, and timestamps keep the reasoning connected to its source.
Explore Evidence forensicsReview confidence, evidence grade, and transcript uncertainty where available. Capture limitations remain visible so missing material does not quietly become a complete story.
Explore Visible uncertainty03 / Reach the right moment
Run focused Studies across the same product. Control the invitation and placement so people encounter the right interview in the right context.
Start from practical interview scripts for onboarding, pricing, switching, or feature validation. Adapt the research goal and flow to your product.
Explore Goals and reusable scriptsUse Study visibility to choose where an interview appears and which widget language it matches. Run multiple Studies with one Project snippet.
Explore Page and language targetingConfigure the in-product launcher or share a direct interview link through your own channels. Invite a participant back for a new interview when you need to follow up later.
Explore Invitations and direct linksAsk eligibility questions before the interview and present recording disclosures before capture starts. Participants choose whether to begin and grant device permissions.
Explore Participant intake and consentPresent the participant experience in English, German, Spanish, French, Japanese, Russian, or Simplified Chinese. Select the widget language for your audience.
Explore A localized interview widget04 / Make the work traceable
Bring related moments together, review what they support, and send a clear product problem to the team that can act on it.
Group related Evidence into a Finding. Refine the problem and its supporting context, check conflicting evidence, and review the sources before deciding it is ready.
Explore Source-linked FindingsExplicitly send a reviewed Finding to Linear product intake or GitHub delivery. Keep the user context and linked Evidence attached to the work.
Explore Linear and GitHub handoffLinear completion resolves the linked Evidence. Review later similar Evidence for possible recurrence. GitHub delivery currently provides the handoff without completion synchronization.
Explore Resolution and recurrence review05 / Connect your tools
Use the dashboard for hands-on review, or connect the same research workflow to an agent and your existing development tools.
Set up Projects, operate Studies, inspect interview sources, and work with Findings through documented interfaces. Agents can request focused source windows instead of guessing from a summary.
Explore MCP, CLI, and APIImport an existing transcript through the API. Access available interview artifacts such as audio, screen recordings, transcripts, and captions for further review.
Explore Transcript import and artifact accessInstall the Project snippet, verify that the widget can load, and test a complete interview before inviting participants.
Explore Installation verificationChoose managed AI or bring your own OpenAI key. Usage-based pricing keeps the cost connected to recorded interview time.
Explore Managed AI or your own keySee it come together
Watch the interview, evidence review, and Finding handoff in a 46-second walkthrough.