Treat video as evidence — with citation-grade transcripts
Bulk transcription, structured claim extraction, 99-language coverage, and timestamps you can cite. Built for researchers whose corpus lives in a URL list — not a folder of wav files.
- What is VidNavigator for researchers?
- VidNavigator for researchers is a reproducible video-intelligence toolkit that transcribes video in 99+ languages, extracts structured claims against a researcher-defined schema, and returns citation-ready timestamps. Built for journalists, academics, and qualitative analysts who treat video as evidence and need exportable datasets.
Research workflows
Investigative journalism
Define a schema like {claim, venue, date, supporting_evidence} and run the Video Data Extraction API over hundreds of candidate-speech clips, interviews, or rally videos. Get back Pydantic-validated JSON with every claim linked to the exact second of the source video for citation.
See the solution →Qualitative research
Export transcripts with timestamps directly into NVivo, Atlas.ti, MAXQDA, or Dovetail. The Universal Transcript Retrieval API returns the same segmented JSON across 9 platforms, so your coding frame does not change based on source.
See the solution →Academic meta-analysis
Index a corpus of conference talks, lectures, or recorded panels, then use semantic Video Search with AI reranking to find every clip that discusses a specific concept across thousands of videos — with timestamp-anchored passages you can cite.
See the solution →Social-science observation
Transcribe TikTok / Instagram / X / YouTube videos at scale, then extract coded fields against your codebook — sentiment, frame, narrative, references, targets — with the Video Data Extraction API for longitudinal studies on how narratives evolve across platforms.
See the solution →Political claim monitoring
Track specific claims and counter-claims in X / Twitter video posts, rally clips, and debates. The Tweet Claim Analysis solution is purpose-built for surface-level verification across short-form video with source-linked evidence.
See the solution →Full-transcript research workflow
For pipelines where the first step is "get me a clean, segmented transcript from any video URL in 99+ languages", the Universal Transcript Retrieval API is the single endpoint — same JSON shape whether the source is YouTube, TikTok, Instagram, Vimeo, or an uploaded file.
See the solution →Reproducibility, built in
- Deterministic transcript IDs. Every transcript has a content_hash so you can detect when a source video has been re-uploaded or edited.
- Retrieval date in every response. Standard practice for web-sourced research — cite the retrieval date alongside the URL.
- Stable segment boundaries. The same video retrieved twice returns the same segment timestamps, so your coding is reproducible against the same evidence.
- Export-ready JSON. A trivial pandas / jq / R pipeline converts our response into NVivo, Atlas.ti, MAXQDA, or Dovetail format.
- Open benchmark methodology. Our methodology paper and harness are public — reviewable and reproducible by the community. Read it.
FAQFrequently asked questions
Build a reproducible video corpus in hours, not weeks.
Bulk transcription, structured extraction, and citation-ready timestamps — behind a single API key.