Krisp provides voice AI infrastructure that processes audio streams in real-time to improve clarity and conversational flow. The platform runs on a unified AI voice engine deployed across 200 million devices, processing over 80 billion minutes of voice conversations monthly.
The VIVA SDK delivers server-side voice isolation specifically designed for voice AI agents. Deployed in the audio pipeline before Voice Activity Detection (VAD), VIVA removes background noise, competing voices, and environmental sounds while preserving only the primary speaker. This architecture directly addresses the false interruption problem that plagues conversational AI. When background sounds trigger VAD as false positives, voice agents interrupt inappropriately or lose track of conversation flow. Krisp reports a 3.5x improvement in turn-taking accuracy when VIVA processes audio before VAD.
The Turn-Taking model predicts when users finish speaking using audio-only input. Rather than relying on silence duration, the model analyzes speech patterns to detect natural turn boundaries, enabling voice agents to respond at appropriate moments without awkward pauses or premature interruptions.
Noise cancellation operates bidirectionally, cleaning both inbound and outbound audio streams. The Background Voice Cancellation model isolates the primary speaker wearing a headset from other voices nearby, solving the cross-talk problem common in home offices and open floor plans. No voice enrollment or training required. Processing runs at 15 milliseconds algorithmic latency.
Accent Conversion transforms speaker accents in real-time while preserving voice characteristics, tone, and personality. Current support covers Indian English, Filipino English, and Latin American English conversion to US English. Latency runs approximately 220 milliseconds, fitting within the 400-500 millisecond one-way latency budget required for natural conversation. The model includes built-in voice isolation, eliminating the need for separate noise cancellation preprocessing.
SDKs support server deployment (Python, C/C++), desktop applications, browsers (JavaScript), and mobile platforms. All processing can run on-device for privacy-sensitive applications. Enterprise certifications include SOC 2, GDPR, HIPAA, and PCI-DSS compliance.
Vapi and Krisp combine to deliver voice agents that handle real-world audio conditions without degraded performance. The integration brings Krisp's voice processing infrastructure into Vapi's voice AI orchestration, addressing the audio quality challenges that cause voice agents to fail in production environments.
For global deployments, accent conversion expands the geographic reach of voice agents. Callers with strong regional accents often experience higher error rates in speech recognition and less natural interactions. Converting accents in real-time improves recognition accuracy and enables consistent agent performance across diverse caller populations.
The technical integration fits Krisp's SDKs into the audio pipeline before Vapi's speech processing. VIVA models integrate with frameworks including Pipecat and Daily. Organizations building voice AI for customer service, healthcare, financial services, and enterprise applications deploy the combined platform. The on-device processing option addresses privacy requirements in regulated industries where audio cannot leave the customer environment.