A customer rarely finishes a sentence cleanly. They ramble, hesitate, repeat.
A VAD-gated chunk recognizer waits for the silence — then decodes — then routes.
A true streaming recognizer emits hypotheses every ~120 ms, so the AI agent can
classify intent, fetch context, and stage a response while the customer is still talking.
The race below uses an identical utterance on both lanes.
Streaming ASRVAD / chunk
Customer utterance · 8.4 s
Turn-based
VAD + chunk decoder
IDLE
— waiting for end-of-turn —
Intent locked at
—s
Response ready at
—s
Streaming
Pramiteeh real-time ASR
IDLE
— ready —
Intent locked at
—s
Response ready at
—s
Run the simulation to see how much dead air a turn-based system creates —
and how Pramiteeh's streaming stack uses that same window to pre-fetch the customer's account, last invoice, and outage status before the question is even finished.