Design the study
Define what to learn, which participants to recruit, and where the script should talk, observe silently, debrief, or speak a transition.
Research operating system for autonomous product teams
UserTold.ai turns real user interviews into evidence your agent can ship against.
Launch interviews inside your product, capture screen and voice, extract reviewable evidence, verify evidence packets, and push evidence-backed work to GitHub or Linear — readable from the dashboard, MCP, CLI, or REST API.
$1 per interviewBYOK inferenceGitHub, Linear, MCP, CLI
Live interview
One conversation becomes one shipping decision
Transcript moment
"I tried this flow three times and still cannot find where to change billing settings."
/settings/billing00:42
Extracted evidence
Struggling moment with strong confidence and source evidence.
TypeStruggling moment
Confidence0.91
Work item payload
{
"title": "Clarify billing settings entry point",
"source": "sig_billing_findability",
"push": "linear",
"watch_for_recurrence": true
}How the loop works
From interview capture to evidence-backed delivery
The point is not to collect transcripts. The point is to create a repeatable operating loop: capture reality, review evidence, route work, then keep resolved evidence connected to future recurrence.
Run the interview
Embed the interviewer inside your product so interviews capture the real screen, voice, transcript, and workflow context.
Extract reviewable evidence
Convert raw interviews into evidence with source quotes, confidence, page paths, and enough context for a human or agent to verify.
Verify and route
Review evidence packets against source context, then push verified work into GitHub or Linear with the quotes and interview context still attached.
Watch for recurrence
When Linear marks the issue complete, resolve the current evidence and watch future interviews for similar evidence that may resurface.
$ usertold init --name "My Product" --format json --yes
$ usertold project use <projectRef> $ usertold project overview Interviews: 24 total (22 completed, 2 active) Evidence: 61 total Work items: 12 total
Source evidence
Review the evidence before your agent writes the work item
UserTold.ai is built so the quote, the source, the confidence, and the resulting work item stay connected. That makes the output useful to both humans and agents instead of collapsing into vague summaries.
Evidence packet
“I expected billing to live under account settings, not workspace settings.”
Interview replay, transcript context, and the exact page path all stay attached to the evidence so reviewers can validate the interpretation.
Interview replayPage pathBehavioral contextWork item link
Issue routing
Push the evidence into GitHub or Linear with source quotes, evidence context, and enough structure for an agent to understand why the work item exists.
Completion sync
When the linked Linear issue is completed, UserTold resolves the current evidence and watches future interviews for similar evidence that may resurface.
Operator visibility
Studies, interviews, and evidence live in one workspace so the whole research loop stays reviewable.
Choose the surface
Use UserTold.ai from the product, the dashboard, or the agent loop
The same research system can live inside your product for real interviews, in the dashboard for review, and inside agent workflows for routing and orchestration.
Embed path
Launch an in-product interviewer with the widget and REST API so real users participate in context.
- Widget embed
- Screen + voice capture
- Study + intake control
Agent path
Let your coding or ops agent design studies, trigger interviews, read evidence, and create work items without touching the browser.
- MCP tools
- CLI --json output
- GitHub + Linear routing
Completion path
Keep delivery connected by syncing Linear completion, resolving current linked evidence, and watching new interviews for possible recurrence.
- Linear completion sync
- Resolved evidence
- Recurrence watch
Pricing and operating terms
Simple pricing for autonomous systems
Platform pricing stays predictable. Model pricing stays on your own provider account. No markup, no hidden research package, and no separation between interview capture and evidence workflow.
Platform
$1 / interview
Prepaid credit packs starting at $10. Interview orchestration, extraction, routing, dashboard review, and Linear completion sync are included.
Inference
BYOK
Bring your own OpenAI key. Your provider account handles inference cost directly, so you keep billing visibility and control.
Common questions
Prepaid credits at $1 per interview, starting with a $10 purchase. Inference costs stay on your provider account through BYOK.
Start the loop
Your agent deserves evidence, not guesses.
Set up a project, embed the interviewer, review the extracted evidence, and route a real pain point into work in under an hour.