Evidence-linked AI
ScribeFlash helps researchers move from raw interview transcripts to findings that remain traceable. Suggested themes, contradictions, and report claims keep a reference to the source quote, transcript segment, timestamp, participant, and research question.
Evidence-linked AI
ScribeFlash
Every finding links back to source evidence
AI suggestions stay marked until reviewed
Quotes can travel into editable reports
The product is designed for UX researchers, product managers, and consultants who need interview insights they can verify before sharing with clients or teams.
When a researcher highlights text, ScribeFlash stores the source segment, timestamp, speaker, interview, and nearby context. The original transcript remains available even when a highlight is deleted.
Evidence can carry multiple tags and one primary research question, so AI analysis stays aligned with the study goal instead of turning interviews into a generic meeting summary.
ScribeFlash can suggest useful evidence and findings, but suggested content is labeled until a researcher confirms, edits, merges, or rejects it.
A strong finding is not just a polished sentence. It can include supporting evidence, counter-evidence, confidence, and limitations so minority views are not hidden as noise.
The evidence workflow is intentionally simple: capture the quote, connect it to the research question, let AI suggest patterns, then decide what belongs in the report.
Select text in the transcript and create evidence with the exact source segment and timestamp.
Add tags, research-question mapping, and notes so the quote has analytical meaning.
Evaluate suggested evidence, themes, contradictions, and confidence before accepting anything.
Move confirmed findings and quotes into an editable report while preserving evidence references.
Trust controls
The product design treats AI as an assistant, not an invisible author. Evidence references, confidence, and limitations help teams review the chain from transcript to final claim.
Traceability
A finding should be able to point back to quote, segment, participant, and interview context.
Human review
Suggested evidence and findings are not mixed with confirmed researcher decisions.
Report integrity
When a finding enters the report builder, the EvidenceReference remains attached for later verification.
Evidence-linked AI means AI-generated findings are connected to the interview evidence behind them: source quotes, transcript segments, timestamps, participants, and research questions.
A normal AI summary can be hard to verify. ScribeFlash is designed so each important claim can be checked against the original interview evidence before it reaches a report.
No. The product design keeps original transcript content separate from cleaned, translated, anonymized, or AI-assisted versions, so edits and derived content do not silently replace the source.
Deleting a highlight removes the research coding for that highlight. It does not delete the original transcript text.
Yes. Findings and quotes are designed to keep EvidenceReferences so a reader can trace them back to the underlying quote, timestamp, segment, and interview.
Upload audio or video, get speaker labels, timestamps, and an editable transcript.
Learn moreCompare participants by research question and surface themes and contradictions.
Learn moreBuild editable reports from confirmed findings with supporting evidence.
Learn moreCreate a project, upload interviews, and keep every important insight connected to source evidence.
