Keep interviews, written feedback and multimedia evidence connected to the records your research team collects. Register permitted sources, import transcripts or descriptive notes, select supporting quotes and organise interpretations with shared codebooks. Give colleagues an evidence trail they can inspect when discussing customer needs, community experiences or programme findings.
Themes lose their context when recordings, transcripts and coding decisions live in separate files.
Connect reviewed text, quotes and coding assignments to the source records that support the interpretation.
Participant stories need a clear evidence trail alongside programme figures.
Retain permitted interview sources and attributed excerpts when reviewing what participants experienced.
Colleagues need to understand why a finding was proposed before choosing the next product experiment.
Review shared codes and supporting quotes together before bringing the finding into a decision.
Use these existing workflows to connect your team’s task with a result it can review and use.
Collect permitted recordings, register the source and import transcript text with any supplied speaker labels and timestamps. Select excerpts and assign the agreed codes.
Explain an interview finding with the supporting text and source record available for review.
Collect participant experiences with consent, connect the permitted sources and organise supplied transcripts or notes using a programme codebook.
Bring documented participant experiences alongside your programme monitoring evidence.
Collect permitted media attachments, register their sources and provide descriptive notes or transcripts. Human reviewers can confirm, correct or reject supplied image captions and classifications.
Keep the reviewer interpretation connected to the media evidence rather than treating an attachment as an automatic finding.
Review quotes and coding assignments, then export supported source, quote, assignment and image-review records as JSON or CSV for your research team.
Give colleagues a structured evidence handoff they can use when preparing the research summary.
Your workflow brings analysis and quality review together in the same workspace. Match the published plan allowances and optional AI credits to the work your team needs.
Ask questions across approved fields, compare relevant groups and organise written responses. Review field meanings, filters, statistical assumptions and supporting answers, then save analyses for the next team discussion.
Use reviewed transcripts, descriptive notes and codebooks to interpret complex evidence. Approved submission text fields also support sampled themes and summaries; check the evidence and collection scope before using a finding.
Provider-assisted dataset questions require workspace enablement, a configured provider, permission and credits. Review the analysis and sampled text themes before using them in a decision.
Investigate configured quality findings, assign follow-up and record review decisions. Apply approved corrections in tracked batches, retain the original submissions and reconsider derived corrections through rollback.
Check source permissions, transcript accuracy and the link between each interpretation and its supporting excerpt. Review collection findings and retain the original submitted records.
Quality flags guide investigation and depend on the available collection metadata. Corrected values are retained separately; submission exports currently contain the original answers.
Keep permitted recordings, photos and videos connected to the records your team collects. Prepare reviewed text and supporting quotes before turning the evidence into a finding.
Collect permitted recordings, import checked transcripts and retain supplied speaker labels or timing. Use quotes and shared codes to explain the interview evidence.
Collect photos alongside structured observations. Review supplied captions and classifications, keeping the human interpretation connected to its source.
Collect video where the device supports it, then supply a transcript or descriptive notes for qualitative review. Keep the recording available as source evidence.
Your team prepares transcripts, descriptions and final research summaries. The current workspace supports media collection and human review; automatic multimedia summary reports are not yet available as a complete workflow.
Explore interview & qualitative researchInterview research needs room for source media, projects and reviewing colleagues. Compare Team for those published allowances and keep sources, transcript revisions, codebooks and review decisions in a shared workspace. Your team supplies the interpretation and final research report; Jorip supports the evidence process behind it.
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Use these measures to evaluate your own improvement. They are not promised customer results.
Define the research question and media permissions. Pilot the form, attachment types and recording support on the devices your team will use.
Register permitted sources and import transcripts or descriptive notes. Check supplied wording, timing and speaker information against the source.
Use shared codes, quotes and reviewer decisions to prepare findings. Export the supported records and prepare the final summary with your team.
Automatic audio, video and image summary reports are not a complete customer-facing workflow. The current screen uses imported transcript text, and image review uses supplied captions or classifications. Approved submission-text summaries do not automatically read media or qualitative transcripts. Qualitative exports do not package the media binaries or transcript revisions.
Choose the service, compare the current plan and test the workflow with your team.
Discuss your team’s requirementsBuild a form for your next survey, application or feedback request. Collect responses in one workspace and give your team a clear place to review them.