• Real-time voice conversations (AI agents)
• Post-call processing (audit, QA, analytics)
• Integrations with CRM, ticketing, booking, payments, internal tools
• Optional on-prem or private-cloud deployments
  
  At Jina, Voice AI is not just about speech recognition or bots answering calls. It is a complete system that handles live conversations, understands intent and context, and converts calls into structured data, actions, and insights. Our Voice AI solutions are designed to plug into your existing systems, operate reliably in real environments, and meet enterprise requirements around scale, security, and deployment flexibility.
  

Technology Stack and Integrations

Our Voice AI systems are built on a flexible, production-grade technology stack designed for real-time performance, accuracy, and enterprise deployment requirements. We select and combine technologies based on latency, scale, compliance, and integration needs rather than relying on a single vendor or model.

Core Voice and AI Technologies

• OpenAI Whisper for high-accuracy speech-to-text across accents and noisy environments
• NVIDIA NeMo for enterprise-grade ASR, TTS, and customizable speech models, including GPU-backed and on-prem deployments
• Hugging Face models for intent detection, sentiment analysis, compliance checks, and domain-specific language understanding
• Custom orchestration layers to manage real-time inference, post-call processing, and evaluation pipelines

Real-Time Voice Infrastructure

• LiveKit for low-latency audio streaming, session control, and real-time voice interactions
• Support for voice activity detection, diarization, barge-in, and interruption handling
• Streaming and batch pipelines for both live agents and post-call intelligence

PBX, VoIP, and Telephony Integrations

• SIP-based PBX systems (cloud and on-prem)
• Asterisk and custom VoIP deployments
• Enterprise contact center PBX platforms
• PSTN connectivity for inbound and outbound calling
• AI-driven IVR replacement or augmentation
• Call routing, transfers, escalations, recording, and replay

Channel and Platform Integrations

• WhatsApp voice and messaging integrations
• CRM systems for lead capture, updates, and enrichment
• Ticketing and support platforms for case creation and escalation
• Booking, scheduling, payments, and internal business tools
• APIs and webhooks for custom system integrations

Deployment and Enterprise Controls

• Cloud, private cloud, and on-prem deployments
• Hybrid architectures with secure edge voice capture
• Encryption, RBAC, audit logs, and retention controls
• Full observability with logs, metrics, and evaluation dashboards

This stack allows us to deliver Voice AI systems that work reliably in real environments, integrate cleanly with existing infrastructure, and scale with your business rather than stopping at demos

Cost Transparency

Voice AI operating costs are usage-based and predictable. In most production deployments, end-to-end Voice AI runtime costs typically range between INR 5 – INR 9 per minute, depending on language support, model selection, concurrency, and deployment choices such as cloud, private cloud, or on-prem. We design systems with built-in cost controls, monitoring, and optimization strategies so scaling remains efficient and free from surprises.