Recordings
Search Recordings
Semantic search over an end user’s transcript chunks
POST
Run a hybrid (semantic + keyword) search across an end user’s transcripts and get back the most relevant excerpts. Each result carries
start_ms/end_ms so you can deep-link a citation back to the moment in the audio. This is the retrieval primitive behind cross-recording AI Ask.
Authentication
Requires an API key withrecordings:read scope.
Request Body
Natural-language search query (1–1000 characters).
End user whose recordings to search (
eu_*). Required unless the API key is itself scoped to an end user.Restrict the search to these recordings. Omit to search all of the end user’s recordings.
Only include chunks from recordings on or after this time (ISO 8601).
Only include chunks from recordings before this time (ISO 8601).
Maximum number of chunks to return (1–50).
Response
Returns the top-K most relevant transcript chunks, best first.Response Fields
| Field | Type | Description |
|---|---|---|
chunk_id | string | Chunk identifier (chk_*) |
recording_id | string | Recording the chunk belongs to (rec_*) |
transcription_id | string | Source transcription (txn_*) |
chunk_text | string | The excerpt text |
speaker | string | null | Dominant speaker label, or null if mixed/unknown |
start_ms | integer | Chunk start offset in the audio (milliseconds) — use for citation deep-links |
end_ms | integer | Chunk end offset (milliseconds) |
recorded_at | string | null | When the recording was captured (ISO 8601) |
score | number | Relevance score (higher is more relevant) |
Search only covers recordings that have a completed transcription — chunking + embedding runs automatically after transcription completes.

