Krisp Voice Translation API

Interesting breakdown of the latency tradeoffs. The language reordering problem is something many demos conveniently avoid discussing. I was wondering how you're handling workload spikes when multiple streams require larger context windows simultaneously. Do you dynamically allocate translation capacity per stream, or is there some form of queueing and prioritization to prevent latency from cascading across tenants?

Krisp launches go wayyyy back. Congrats on the latest. :)

Curious how deep the localization goes. Spanish in Mexico and Spanish in Spain can feel quite different in everyday use. Do you support regional variations like that?Congrats on the launch!

Real-time speech-to-speech is the hard part - what's the round-trip latency at acceptable quality? Most translation APIs I've tested hit 800ms+ which is fine for async but breaks conversational flow completely.

How well does Custom Vocabulary / Dictionary work? How many terms can I add, and does it slow things down?

Congrats on the launch! 🚀 Real-time voice translation is impressive on its own, but production experience in healthcare and finance makes it even more compelling. Best of luck today!

Real-time speech-to-speech at API level means you've solved the three-stage pipeline problem: ASR accuracy, translation context, and TTS naturalness all simultaneously. We've built on streaming audio APIs and the hardest part is always mid-utterance interruptions breaking the translation context. What's your P99 latency for a 10-second utterance, and how do you handle speaker turn overlap?

So proud of this launch!

Congratulations! I will definitely try it.

Great to see this finally launched. Super useful update to a great tool!

Looking forward to seeing what the Product Hunt community builds with it. We'd love your feedback!

Impressive to see accuracy claims based on real contact center traffic instead of lab conditions. How does the API handle industry-specific terminology, like healthcare or financial services vocabulary, where a single mistranslation can create major issues?

The "works great in demos, then real users show up with background noise and accents" line is exactly the wall we hit building voice AI for older adults. Phone-quality audio and unfamiliar accents break most pipelines that benchmark beautifully. Training on a million real contact-center calls is a smart moat for that reason. One question on the speech-to-speech path: how much added latency does translation introduce over plain transcription, and is it low enough to keep a live call feeling like a natural back-and-forth?

Hey Product Hunt!

We've been running real-time voice translation in enterprise contact centers. Healthcare, insurance, finance. Calls where a wrong word means a patient safety incident or a compliance violation.

That pressure built an engine most benchmarks can't replicate. 96% accuracy on live calls with real accents and noise. Zero patient safety incidents across 8+ languages. Over a million minutes of production translation.

Today we're opening that engine up as a self-serve API. Same model, same accuracy, same 61 languages. Python and JS SDKs, playground with 60 free minutes, custom vocabulary and translation dictionaries from day one. No sales call.

If you're building anything where voice crosses a language barrier and accuracy matters, hear it yourself: https://lab.krisp.ai/products/vo...

Our team will be here all day. Ask us anything.