Decision layer for voice AI
Delaware, USA
Joined October 2026
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Today marks the day after which every voice agent will start listening.
Your voice agent can get every word right and still get the call wrong.
Introducing Tazo (@TazoLabs), an audio decision model for live voice agents. Speech in, decision out.
Give it raw call audio, a text prompt and your options. It returns the calibrated probability for each option, directly from audio.
• 70.9% vs 46.4% for STT + Jev on real production calls
• Ranks #2 on audio intelligence benchmark (MMAU)
• <200 ms model latency
• First decision model tuned to run on streaming voice calls
• Introducing “None of the above” option to handle out-of-scope and unsure states.
API is live. Free credits for every new sign-up.
Give your agent ears @ app.tazolabs.com
See it in action below 👇
Tazo Labs retweeted
I think the biggest gap in voice AI is that agents make decisions from a transcript, not from the audio. I wrote down my thoughts.
I’d love to hear where you disagree.
Is Jev useful for voice agents? Hell Yeah!
Is it good enough? Veris thinks so, 52% to 11% mis-interpreting cutting off.
With audio as an input, the number goes down to sub 5%.
Disclaimer: internal benchmarks on Tazo.
veris.ai/blog/jev-turn-detec…
Has anyone heard of an audio decision model ? Or as critics are calling it “a glorified generalised classifier”