English

Purpose-built video transcription tool for content teams and researchers. It ingests video files and outputs text with optional time alignment and speaker labeling. The system supports batch processing of large libraries and can preserve contextual cues such as pauses and emphasis when available. It is suitable for journalists, educators, podcasters, marketers, and accessibility specialists who require fast turnaround and reliable transcripts.
The core pipeline converts audio to text using advanced ASR models, followed by optional diarization to assign segments to speakers. Punctuation restoration and capitalization improve readability. Time alignment enables single-file transcripts and captions in SRT or VTT formats. Outputs can be used for searchable transcripts, subtitles, or as a dataset for training or QA workflows. The tool handles various languages and accents, with language hints guiding decoding.
Differentiators include privacy-first processing, chunked long-file handling for efficiency, and flexible export options including JSON with word-level timestamps and confidence scores. It integrates into media production pipelines, education platforms, and research repositories. Use cases include post-production captioning, conference recordings, lecture capture, and archival of interviews. It does not perform live transcription; it processes uploaded content and returns results quickly with structured metadata.
Common scenarios and examples: a university lecture captured at 2 hours, with two speakers; a panel discussion with multiple languages; a documentary clip with noisy audio; retrieval and indexing of key topics from a filmed interview.