ai-coustics vs Krisp

ai-coustics is built for production Voice AI - conditioning raw audio into stable, machine-ready input beneath your ASR, LLM and TTS.

Real-time speech enhancement tuned for ASR accuracy, not just human perception

Primary speaker isolation built for voice agents: background voices and media audio no longer corrupt turn-taking.

Audio insight into every call: score contact-side audio quality before a bad transcript becomes a support ticket

No ONNX dependencies to wrangle - drop the SDK in and you're running in seconds

Free 30-day self-serve SDK trial: unlimited usage, including in production

Zero data retention - no customer, personal or audio information being transferred

Try it free

Powering voice AI across Europe & North America

How do the two solutions compare?

We compare the model offering, ease of integration, privacy and more in the blog below.

See the full breakdown

Strip noise, reverb and artifacts from live audio and hand your model clean, machine-ready input — on every call, in real environments.

Lock onto the target speaker and detect speech accurately, so agents stop interrupting and turn-taking stays clean in noisy, multi-voice settings.

Get real-time or post-call insights into whether the audio reaching your agent is likely to cause failure before you need to look at a transcript.

Get real-time or post-call insights into whether the audio reaching your agent is likely to cause failure before you need to look at a transcript.

Rather than competing with ASR, LLMs or TTS, ai-coustics makes them reliable - from the moment audio leaves the real world.

Perceptual scores tell you how audio sounds to a person. These tell you how it performs inside a Voice AI pipeline.

Raw

Quail Voice Focus 2.2 S

Quail Voice Focus 2.2 L

lower % is better

Left part: Deletions / Middle: Substitutions / Right: Insertions

	AssemblyAI	Deepgram	Soniox	Mistral	Cartesia	Gladia	Speechmatics	Gradium
Raw	50.1%	74.8%	80.0%	40.5%	51.4%	50.8%	68.5%	53.0%
Voice Focus 2.2 S	17.0%	17.3%	13.1%	13.3%	16.3%	13.2%	12.6%	18.1%
Voice Focus 2.2 L	14.8%	16.4%	12.5%	12.5%	15.3%	13.0%	11.7%	16.1%

Trusted by Voice AI teams to deliver production-ready speech enhancement in real-time.

"Audio that sounds fine to a human can be completely broken for a machine. Being able to prove that at scale changes everything."
Jeechieu Ta
Software Engineer, Phonely
“At our scale, audio quality isn't a detail. It's the difference between converting a customer and losing one. ai-coustics gives us the clarity our agents need to perform at volume.”
Seb Hapte-Selassie
Co-founder, telli
"Voice cloning is highly sensitive to acoustic inconsistencies. Using ai-coustics to clean audio upstream simplifies modeling and keeps speaker identity stable."
Adam Froghyaria
Senior Research Engineer, Synthesia
"The adoption process was effortless. It was engineer to engineer on Slack. No bureaucracy. Just real conversations and fast progress."
Stephan Nöthen
Principal Product Architect, Elgato
"With ai-coustics on, we've had the best customer satisfaction scores of all the tests we've done."
Razvan Kusztos
VP of Engineering, PolyAI

"Audio that sounds fine to a human can be completely broken for a machine. Being able to prove that at scale changes everything."
Jeechieu Ta
Software Engineer, Phonely
“At our scale, audio quality isn't a detail. It's the difference between converting a customer and losing one. ai-coustics gives us the clarity our agents need to perform at volume.”
Seb Hapte-Selassie
Co-founder, telli
"Voice cloning is highly sensitive to acoustic inconsistencies. Using ai-coustics to clean audio upstream simplifies modeling and keeps speaker identity stable."
Adam Froghyaria
Senior Research Engineer, Synthesia
"The adoption process was effortless. It was engineer to engineer on Slack. No bureaucracy. Just real conversations and fast progress."
Stephan Nöthen
Principal Product Architect, Elgato
"With ai-coustics on, we've had the best customer satisfaction scores of all the tests we've done."
Razvan Kusztos
VP of Engineering, PolyAI