Build AI-powered voice agents that handle phone calls, understand natural speech, and take real actions — from booking appointments to qualifying leads — without putting callers on hold.
Every AINinza voice agent follows a seven-stage pipeline that converts spoken words into intelligent actions and delivers a natural response — all in under two seconds end-to-end.
Speech Input
Caller speaks naturally over phone or VoIP
ASR (Speech-to-Text)
Whisper, Deepgram, or Azure Speech converts audio to text in real time
Intent Detection
NLU classifier identifies caller intent and extracts entities
LLM Reasoning
Language model generates contextual response using RAG and business logic
Action / API Call
Agent executes actions — CRM update, booking, order lookup
TTS (Text-to-Speech)
ElevenLabs or Azure Neural TTS converts response to natural speech
Speech Output
Caller hears a human-like response in under 2 seconds
60–80% call containment rate — most calls resolved without human transfer
50% reduction in average handle time through instant intent detection and automated actions
24/7 availability with zero hold times, even during peak call volumes
AINinza builds voice agents on a modular, carrier-grade stack optimised for sub-second latency, natural-sounding speech, and reliable telephony integration. Every layer is independently swappable so clients avoid vendor lock-in.
The ASR layer converts caller speech into text in real time. AINinza selects the best engine based on language, accent, and latency requirements.
Natural-sounding TTS is critical for caller trust. Robotic voices increase hang-up rates by 35–50%.
AINinza handles the full telephony layer so voice agents work on real phone networks, not just demo environments.
The same model-agnostic gateway AINinza uses for chatbots powers voice agents. All model calls route through a FastAPI gateway with automatic retries, fallback chains, and token-level logging.
< 2s
End-to-End Latency
30+
Languages Supported
99.9%
Uptime SLA
Traditional IVR systems force callers through rigid menu trees. AI voice agents understand natural language from the first second — no “press 1 for sales” required.
AINinza follows a structured delivery process that takes voice agent projects from discovery to production with defined milestones and client review gates at every stage.
We analyse your existing call recordings, IVR logs, and support ticket data to identify the highest-impact voice automation opportunities. The output is a prioritised use case matrix with estimated containment rates and ROI projections.
We design the agent's conversational style, select the TTS voice, and script responses for common scenarios. This phase also defines escalation triggers, barge-in handling, and silence detection thresholds.
Engineers build the full ASR → LLM → TTS pipeline, integrate telephony and CRM systems, and run the agent through 200+ test call scenarios covering happy paths, edge cases, and adversarial inputs.
The agent launches at 10% of call volume. AINinza monitors containment rate, caller satisfaction, and intent detection accuracy daily — tuning prompts, adjusting confidence thresholds, and expanding scope until the agent handles 100% of target call types.
60–80%
Call Containment
< 2 sec
Response Latency
50%
Handle Time Reduction
2–3 mo
Typical Payback Period
Transparent pricing for AI chatbot development — from single-channel bots to enterprise multi-channel deployments.
Learn moreAI solutions purpose-built for customer service teams — chatbots, voice agents, and intelligent routing.
Learn moreCustom LLM-powered chatbots for support, sales, and operations — deployed in 4-8 weeks.
Learn moreShare your call volume and top call types, and we'll propose a phased voice agent rollout with containment targets and ROI milestones.
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