User research repository
Your user research repository.
Keep the evidence connected.
Bring interviews, transcripts, clips, and findings into a shared research repository. Help your team find what participants said and understand the evidence behind a decision.
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A research repository that starts with your interviews
A user research repository gives your team a place to organize and reuse what it learns. Tetra connects the recording, the transcript, the moments you highlight, and the findings you share, so the context stays with the research.
Collect
Upload existing recordings or capture new interviews with TetraBot. Keep sessions and research documents together in a project.
Organize
Use tags to describe recurring topics and custom fields to add context to sessions, projects, and insights.
Retrieve
Search across projects, sessions, snippets, and insights when a new question calls for previous research.
Keep findings connected to their source
Save a meaningful moment as a snippet, add a note explaining why it matters, and connect it to an insight. An insight brings the conclusion and its supporting snippets together. Teammates can review the evidence instead of relying on a summary alone.
Use AI interview analysis to explore transcripts and suggest useful moments, then review the results before adding them to your research.
Team invitations need to be easier to discover.
Maya expected an invitation control alongside the project.
Give saved excerpts a research vocabulary
In Harbor’s onboarding study, tags such as “Invitation friction” and “Delayed kickoff” connect related moments from Maya’s and Jonah’s interviews. Filter by a tag to find the relevant excerpts, then open the context behind each one.
“I kept looking on the project page.”
“I searched the help page before I found invitations in settings.”
“We started the project the next morning instead.”
A tag groups related material; it does not establish a finding by itself. Review the surrounding interview, compare the relevant excerpts, and explain the interpretation when you turn that evidence into an insight.
From one study to your team's next question
Consider an onboarding study. Your team interviews new customers about where they get stuck. This illustrative workflow shows how the repository can keep that research useful:
- Keep the study together. Store its guide and interview sessions in a project, with fields describing the study and participants.
- Save the moments that matter. Tag clips about account setup, invitations, and first use. Write notes that explain what each clip contributes.
- Build an evidence-backed finding. Group relevant snippets into an insight and explain the pattern, including any conflicting observations.
- Return to the evidence. When the team revisits onboarding, search for the relevant sessions and findings rather than starting from a folder of recordings.
Questions before you start
- How is a research repository different from storing recordings in folders?
- Folders store files. A research repository also connects transcripts, tags, selected quotes, and synthesized findings, making it easier to retrieve both a conclusion and the material behind it.
- Can we start with interviews we already have?
- Yes. Upload existing recordings to a project and build your repository as you analyze them. You can also use TetraBot to capture new interviews.
- Does AI chat search every project in the repository?
- Repository search helps you find material across your workspace. AI chat works with the interviews included in its project conversation; it is a separate way to explore selected research.
- Do we need to recruit participants through Tetra?
- No. You can work with your own participants and existing recordings. Participant sourcing is available when you need it and is priced separately.
Try it with your next research project.
Start with existing interviews or recruit participants for a new study. Choose the workflow that fits your team.
Participant recruitment is priced separately. See pricing for plan details.