Rev
Transform audio/video to text, enhance global accessibility, quick and accurate.

About
Rev provides a platform for converting spoken content from audio or video into precise, readable text. With both AI-powered and human transcription options, users can select the right balance of speed, accuracy, and budget for their projects. The system supports rapid processing and can deliver results within hours, making it suitable for time-sensitive work.
Accessibility is at the forefront with tools to add captions and subtitles to videos, catering to audiences with diverse language needs and those requiring FCC and ADA compliance. The platform’s app allows users to record and begin transcribing content while on the move, streamlining workflows for busy professionals.
Serving a broad user base, Rev assists organizations and individuals alike—be it transcribing legal evidence, preparing international lecture material, or publishing searchable podcasts. The service is pay-as-you-go, allowing flexible use for both occasional and large-scale needs.
Who is Rev made for?
Rev is most valuable to professionals and teams that regularly handle audio or video content requiring accurate transcriptions or captions. Journalists and newsrooms use it to quickly prepare transcripts of interviews, press conferences, and broadcasts, which aids in both reporting and content archiving.
Legal professionals benefit by obtaining precise transcripts of client meetings, court recordings, or interviews, facilitating efficient documentation and evidence management. Content marketers, YouTubers, and online educators leverage the service to add captions or subtitles to videos, improving accessibility and reaching wider, multilingual audiences.
Researchers conducting qualitative interviews, podcasters aiming to publish searchable transcripts, and support teams needing to document customer interactions can also streamline their workflow with Rev’s offerings. The platform is practical for anyone managing content that needs to be both accessible and easily referenced in text form.