Voice AI is only as strong as its audio foundation. Agents fail because the real-world audio feeding the stack is messy: background noise, a reverberant room, a second speaker cutting in, a call recorded over a weak connection... These issues cause ASR errors, missed turns, and hallucinations further down the stack.

If you're building a voice agent and searching for noise cancellation, speech enhancement, or background voice cancellation tools, you've likely come across both Krisp and ai-coustics. But what each one actually offers, where they overlap, and where the Krisp alternative built specifically for voice agents differs from a platform that started in conferencing?

In this guide, we’ll break down the two solutions to see what suits you best.

Krisp and ai-coustics: short overview

ai-coustics builds the audio intelligence layer for Voice AI. Our SDK turns noisy, unpredictable audio into stable, machine-ready input for the ASR, LLM, and TTS systems behind a voice agent, running on-device. Teams already using ai-coustics in production include PolyAI, telli, and AssemblyAI, alongside voice AI companies across customer support, healthcare, and consumer agents, processing millions of minutes every week.

Krisp today spans three products: Meeting AI for conferencing, Call Center AI for contact centers, and VIVA, its Developer Voice AI SDK for teams building voice agents. VIVA already processes more than 12 billion minutes of voice AI agent traffic a year and runs inside more than 130 production voice AI products, by Krisp's own count.

Getting started: access, pricing, and support

The fastest way to know if a Krisp alternative is worth switching to is to try it on your own audio, in your own stack, without a massive time investment.

ai-coustics offers a free 30-day self-serve SDK trial. It's unlimited, including in production, and doesn't require a credit card to start. You generate a key in ai-coustics’ developer platform and start processing audio in minutes. Krisp's Developer SDK works differently. Exploring models in Krisp's playground doesn't require signup, but moving to actual SDK integration goes through a "Request SDK Access" form and a sales conversation before you get to production.

Pricing follows the same pattern. ai-coustics offers monthly tiers starting at $150/month, scaling up through Pro and Business tiers, with custom Enterprise pricing above that. Krisp's Developer SDK tiers (Early Stage and Enterprise) aren't published - both are apply-only and quote-based.

ai-coustics doesn't gate support behind a plan tier at all: everyone has access to our support and community on Discord. Higher tiers add a dedicated Slack channel and personalized benchmarks on your own audio, but you don't need to be on an Enterprise contract to get a detailed answer from the team building the models. Krisp also has a Discord server and names dedicated engineering support and custom SLAs specifically at its Enterprise tier.

If you want to test on your own audio today, without a sales call first, the ai-coustics trial gets you there in minutes. If your team is already running an enterprise procurement process and cares more about a negotiated SLA than speed to a first test, Krisp's Enterprise is also a good fit.

Model coverage: enhancement, isolation, detection, and insight

Krisp splits its models by use case: an RTC SDK for human-to-human calls, and a separate VIVA SDK built specifically for voice AI agents. ai-coustics focuses on models for Voice AI pipelines and offers a human-to-human enhancement model, Rook, as a side product.

Speech enhancement

Classic speech enhancement models are best suited for teams dealing with noisy audio conditions in use cases with more than one speaker.

ai-coustics’ Quail handles real-time speech enhancement tuned for ASR and STT accuracy. It's built for human-to-machine audio: single- or multi-speaker, near- or far-field, and it deliberately leaves some background noise and reverb in the signal, since that acoustic context can help an STT model transcribe more accurately. That is why it drops word error rates by up to 25% in our testing. It ships in four configurations: Quail L at 16kHz (35 MB) and 8kHz (33.4 MB) for the highest quality, and Quail S at 16kHz (8.88 MB) and 8kHz (8.43 MB) for lighter deployments, all at the same 30ms latency.

Krisp's closest model is Noise Cancellation (NC), originally created for human-to-human communication - although it's also available through LiveKit's livekit-plugins-noise-cancellation package. It removes all environmental background noise rather than keeping any of it.

Speaker isolation

Interfering voices are one of the biggest causes of agent failures. Quail Voice Focus isolates the primary speaker from background voices, cross-talk, and media audio. It's a small, real-time model: the flagship Voice Focus 2.2 L runs at 20 MB, with a 2.2 S variant at 5.04 MB for lighter deployments, both at 16kHz (with 8kHz support) and a 30ms end-to-end latency. In per-provider testing, it's cut word error rates from 65.8% down to 12.5% on Speechmatics, 52.9% to 16.8% on Cartesia, and 48.3% to 15.1% on AssemblyAI, reducing WER up to 84%.

Krisp's answer is Voice Isolation which folds noise cancellation and non-primary-speaker removal into a single model rather than shipping them as two. Krisp also offers a lite variant of Voice Isolation at roughly 70% less compute, for teams that need a lighter footprint. It results in a 46.4% average WER reduction across tested conditions, rising to 69.7% in competing-speaker scenarios, tested across 10 STT systems from seven vendors.

Voice activity detection and turn-taking

ai-coustics offers more than one VAD model, and both are purpose-trained for the job rather than inferred as a side effect of enhancement. ai-coustics VAD 2.1 is a general-purpose, noise-robust detector: it flags any audible speech, no matter who's talking, which makes it the right choice for multi-speaker environments. VAD Voice Focus is conditioned on the primary speaker specifically, so it ignores interfering voices and background noise. That second one is the one that matters for voice agents in noisy environments, where a general VAD will trigger on whoever's talking near the mic, not just your caller. Both are small and fast - VAD 2.1 is 634 KB with a 30ms algorithmic delay, and VAD Voice Focus is 1.44 MB at the same latency - and allow tuning to your specific needs.

Krisp's VAD ships under VIVA as a single general speech/silence detector with a configurable threshold. Its public docs don't publish the latency, size, or accuracy numbers but Krisp stands out with additional tools: Turn Prediction and Interruption Prediction. Both are audio-only models that decide when a speaker is done or being interrupted without needing a transcript first.

Audio insight

Tyto is ai-coustics' audio intelligence model. It listens to the audio flowing into a voice AI stack and scores it across six dimensions: background noise, reverberation, speaker loudness, interfering speech (incl. background media), packet loss, and codec degradation introduced by the transmission chain itself. Used after a call, it flags which ones are worth investigating before a bad transcript turns into a support ticket. Used in real time, it can tell an agent when the audio itself is the problem, so it can be fixed in the moment. Nothing in Krisp's current lineup, or anywhere else in the voice AI space, does this.

Read more on our model documentation or the individual Quail Voice Focus and Tyto posts for the technical detail and benchmarks.

Integration: dropping into a stack you already run

The ai-coustics SDK has no ONNX dependency and no heavy runtime to configure. That's because we use AirTen, our purpose-built neural network runtime for real-time audio inference, written in dependency-free Rust and small enough to run on a microcontroller. Tested against ONNX Runtime on an NXP i.MX 91 processor, AirTen ran up to 2x faster on worst-case execution time, used 80% less RAM, and guaranteed sub-8ms inference at 48 kHz, all in a runtime under 1 MB. In most stacks, integration is just a simple code addition and we provide code examples. Our models run CPU-only, and are available as Python, Node.js, Rust, C, C++, and WebAssembly wrappers.

We maintain a native LiveKit plugin that drops enhancement and VAD directly into LiveKit's audio pipeline plus a Pipecat integration, so enhancement is easily added into your existing pipeline. And a self-serve trial key is available the moment you sign up to the Developer platform, so you can test on your own audio, in production, within minutes.

Krisp's VIVA models also run on standard CPUs with low, although undisclosed, latency. Krisp ships its own native LiveKit and Pipecat integrations, backed by public sample apps and code-first docs. But generating an API key to run it in a custom stack goes through a "Request SDK Access" form and a sales conversation. Krisp does publish accuracy numbers for individual VIVA models, like the Voice Isolation WER figures above, but we couldn't find a published end-to-end latency number for the VIVA SDK itself the way we publish 30ms across our own models.

Privacy

ai-coustics is born and raised in Berlin, Germany, and its primary cloud infrastructure runs in the EU. The SDK processes audio locally, on-device. Audio, recordings, buffered samples, transcripts, and model input or output never reach our servers. What does get sent is pseudonymous product telemetry: SDK version, model ID, OS and CPU architecture, seconds of audio processed, and whether VAD is active, metered against your license key. Full detail is in our SDK telemetry documentation.

Krisp is headquartered in Berkeley, California, and relies on the EU's Standard Contractual Clauses to transfer EU user data to the US. It makes a similar on-device claim for its noise cancellation feature specifically, stating in its privacy policy that it doesn't access or store audiovisual data for that feature; its policy doesn't spell out the same detail for VIVA. Krisp does hold SOC 2, HIPAA, and PCI-DSS certifications.

For teams in healthcare, legal, or finance evaluating a voice agent vendor, privacy and data handling are important. On-device processing secures your audio - and if your compliance needs go beyond what's covered here, that's a direct conversation with our team, not a dead end: get in touch and we'll work through what your specific requirements need.

Krisp or ai-coustics: which one fits you best?

Despite coming from different backgrounds, both companies are now building specifically for voice AI agents. Krisp's VIVA covers Voice Isolation and VAD, plus a pair of turn-taking models. ai-coustics covers the same enhancement and detection ground with Quail, Quail Voice Focus, and two dedicated VAD models, and adds a category neither Krisp nor most of the market ships yet: Tyto, scoring the audio itself for the conditions that cause failures downstream, in real time or after the call.

If you're building a voice AI agent and want self-serve access to models built specifically for what an ASR and an LLM need from audio, plus a category, audio insight, that nothing else on this list offers, that's what ai-coustics is for.

The fastest way to find out is to run it on your own audio. Test it for free now or talk to us if you have any questions.