Security
ScribeFlash is designed for sensitive customer interviews: project-scoped processing, source-preserving evidence, clear AI boundaries, and user-controlled retention and deletion.
Security
ScribeFlash
Project data is processed for the project you create
Original transcripts remain separate from AI-derived versions
Deletion and retention controls are part of the workflow
Security content should be specific and verifiable. These controls describe how the research workflow is designed, without making unsupported claims such as “100% accurate” or “fully compliant.”
Analysis uses the project goal, research questions, transcript segments, participant identifiers, language, and confirmed evidence for the active project. It is not designed to mix unrelated account data or other projects into the analysis.
Researchers can edit speaker names, transcript text, timestamps, and terminology, while the original transcript remains separate from cleaned, translated, anonymized, or AI-assisted versions.
Findings are expected to reference existing transcript segments, and quotes should match the original source text. This helps teams catch citation mistakes before client-facing reports are exported.
Users decide whether project data should be retained or deleted. Deleting a project disables access and queues cleanup for related media, exports, cache, and project content.
The ScribeFlash workflow separates upload, transcription, evidence review, AI analysis, reporting, export, and deletion so users can understand where data is used.
The researcher defines the study goal, client context, research questions, and output language.
Audio or video files are processed asynchronously for transcription, speaker labels, timestamps, and review.
Researchers edit transcripts, highlight key quotes, assign tags, and confirm evidence before analysis.
Confirmed findings move into reports and exports; users can choose retention or deletion when the project is done.
Trust controls
ScribeFlash avoids unverifiable marketing claims and focuses on the controls that matter in research work: source traceability, human review, and clear limitations.
No absolute accuracy claims
The product does not promise “100% accurate” transcripts or analysis. Researchers review and correct important content.
AI remains reviewable
Suggested findings, evidence, confidence, contradictions, and limitations are presented for researcher review.
Minority views are preserved
Contradictions and counter-evidence can remain visible instead of being flattened into the dominant theme.
Third-party processing disclosure
AI and transcription providers should be described in the data processing agreement or relevant privacy documentation.
No by default. The product design scopes analysis to the active project: its research goal, research questions, transcript segments, participant identifiers, language, and confirmed evidence.
Yes. The workflow includes project retention and deletion controls. Deleting a project disables access and queues cleanup of related media, exports, cache, and project content.
No. Interview transcripts and AI findings should be reviewed by the researcher. ScribeFlash is designed to make errors easier to catch by preserving source references and evidence links.
Findings are designed to keep EvidenceReferences to transcript segments, quotes, timestamps, and interviews. Suggested content is labeled until a researcher confirms, edits, merges, or rejects it.
No. Original content is kept separate from cleaned, translated, anonymized, or AI-assisted versions, so source material can remain available for verification.
Start with a project workflow that makes source evidence, AI suggestions, and deletion decisions visible.
