Krisp is a commercial deep-learning noise-suppression SDK widely embedded in meeting and contact-centre applications to strip background noise from both sides of a call. Its neural models are heavier and generally more capable than lightweight open-source options like RNNoise, removing complex, non-stationary noise — typing, dogs, cafe chatter, other voices — while keeping the target speaker clear, and newer versions also tackle echo and room reverberation. It runs on-device for privacy and low latency. Krisp is representative of a wave of AI audio-cleanup products that became standard in remote work; the engineering question when adopting one is the balance of quality, CPU cost, and the risk of over-processing artefacts.
The book · Volume 4 of 7
Audio for Video: A Complete Guide to Sound in Video Products: From PCM and Codecs to Loudness, Accessibility, and Real-Time Voice Processing
Krisp is the noise-suppression SDK many meeting apps license, and the build-or-buy decision around it shapes call quality and cost. Volume 4 puts Krisp in context with real-time voice processing: classical noise suppression, RNNoise and neural models, echo cancellation, AGC and VAD, and where each runs in the pipeline. Written by Nikolay Sapunov, CEO at Fora Soft.
Deciding between Krisp and an open-source noise suppressor for your calling app?
We will compare Krisp, RNNoise and DeepFilterNet on your audio and platforms and give you a recommendation with latency, CPU and licence cost. 250+ video products shipped since 2005.
