Audio semantic search

Find the moment by describing it, across a whole audio archive, with no manual tagging first. Results are returned as timecoded segments, so a search over thousands of hours lands on the passage rather than on the file. Indexing runs once over the archive, after which new queries return in seconds without reprocessing the audio.

You can use the models we operate or bring your own model and we run it on your cluster. Work arrives as an API call, a batch over a folder or bucket, or a resident on-premise service, and results return as structured output with a per-job audit record.