Voice AI Solutions
Voice interfaces that actually work.
Real-time transcription, conversational AI, and voice-driven workflows — built for production, not demos.
We design and ship voice AI systems that handle real calls, real accents, real background noise, and real conversation flows — including interruptions, clarifications, and graceful escalation to a human when the situation requires it. From the audio pipeline through the conversation logic to the CRM integration, we own the full stack.
What we build
Voice AI is a stack of interdependent systems — audio transport, speech recognition, language understanding, response generation, text-to-speech synthesis, and conversation state management. A failure at any layer degrades the entire experience. We design all of it together.
STT / TTS Pipelines (Whisper, Deepgram)
Speech-to-text is the entry point where most voice systems fail — wrong transcription means wrong intent means wrong response. We select and configure transcription providers based on your latency requirements and audio characteristics: Whisper for offline or batch transcription where accuracy is the priority, Deepgram for real-time streaming transcription where sub-200ms latency defines the user experience. On the output side, we match TTS providers — ElevenLabs, Cartesia, or others — to the voice quality and latency requirements of your use case.
Voice Agents (Vapi, ElevenLabs, Cartesia)
We build conversational voice agents that follow dynamic dialogue flows, maintain conversation context across turns, handle interruptions and topic changes gracefully, and integrate with backend systems to take actions during the call — looking up records, updating CRM fields, booking appointments, or escalating to a live agent with a structured handoff. These agents are not scripted IVR trees; they understand intent and adapt to what the caller actually says.
Real-Time Conversation Systems (LiveKit, WebRTC)
Real-time voice requires low-latency audio transport. We architect these systems on LiveKit and WebRTC — handling audio capture, noise suppression, echo cancellation, and streaming to the transcription and inference layers with latency budgets that keep the conversation feeling natural. We design for the full round-trip: audio in, transcription, LLM inference, TTS synthesis, audio out — optimized so the gap between the caller finishing a sentence and the agent responding is measured in hundreds of milliseconds, not seconds.
IVR Replacement
Traditional IVR systems are rigid, frustrating, and unable to handle anything outside their scripted paths. We replace them with conversational voice agents that understand natural language, handle variation in how callers express intent, and complete tasks the old IVR routed to human agents — without requiring callers to navigate menu trees or repeat themselves after every misrecognition.
Voice-Activated Internal Tools
Hands-free voice interfaces for internal workflows — field technicians who need to log work without stopping to type, warehouse staff querying inventory, clinicians dictating notes directly into structured records. We design voice-activated tools that integrate with your existing systems and translate spoken inputs into structured actions.
Multilingual Support
For organizations serving multilingual populations, we build voice systems that detect language automatically and respond in kind — or that are specifically configured for non-English primary languages. We select transcription and synthesis components based on their actual performance in your target languages, not their claimed language support lists.
Where voice AI delivers
Voice AI earns its place when the alternative is a human handling a high volume of repetitive, structured conversations — or when a keyboard and screen are physically unavailable or impractical.
Inbound call handling for common support requests — status checks, FAQs, account updates, appointment scheduling — that do not require a human agent. Voice agents that resolve calls at first contact and escalate with context when they cannot.
Voice interfaces for users who cannot or prefer not to interact with screens — older adults, users with motor impairments, or any context where voice is the primary or preferred modality. We design for intelligibility and patience, not speed.
Technicians, inspectors, and field workers who need to log information, retrieve data, or communicate status without stopping work to type. Hands-free voice interfaces that connect to your backend systems and keep field staff in motion.
Clinical documentation via voice — structured note dictation, SOAP note generation, and encounter summaries that reduce the documentation burden on clinicians without sacrificing accuracy or compliance. Built to HIPAA standards with no PHI leaving the clinical environment.
How we build voice AI systems
Voice AI systems fail in ways that are easy to miss during demos. We test against real conditions — noisy environments, overlapping speech, unexpected inputs, network degradation — because that is what production looks like.
Latency budget design
We design the round-trip latency budget before we select components — knowing that transcription, inference, and synthesis each consume a portion of the time budget, and that exceeding it makes the system feel broken regardless of how accurate it is. Every component is selected and configured to fit its allocated budget.
Conversation flow design
We design dialogue flows that handle the real range of what callers say — not just the happy path. Interruptions, topic switches, clarification requests, silence, and hostility are all inputs the system needs to handle gracefully. We build conversation graphs that account for these cases and test them with adversarial inputs before deployment.
Backend integration
A voice agent that cannot take action is just a chatbot with a microphone. We integrate voice agents with CRM systems, databases, scheduling platforms, and any backend system the agent needs to query or update during a call. Tool calls happen during the conversation, not after it.
Observability and quality monitoring
We instrument every voice deployment with call recording, transcription storage, intent classification logging, and outcome tracking. This gives you the data to evaluate agent performance, identify where conversations go wrong, and improve the system over time. For regulated environments, the same infrastructure satisfies audit and compliance requirements.
Why AR Data
Voice AI is latency-sensitive in ways most systems are not. A 200ms round-trip sounds natural; 800ms breaks the conversation. We design the latency budget first — allocating time across transcription, inference, and synthesis — and select components that fit it. We have built across the full voice stack: STT with Whisper and Deepgram, TTS with ElevenLabs and Cartesia, orchestration with Vapi, and real-time audio transport with LiveKit and WebRTC. We know where the failure points are because we have hit them.
The 20+ years of enterprise delivery behind every AR Data engagement means we understand integration at the level voice agents actually require — telephony systems, CRM platforms, EMRs, and the authentication and compliance constraints that come with regulated environments. We have built for healthcare, financial services, and field operations, where HIPAA and data residency requirements are non-negotiable, not afterthoughts.
We deliver on fixed-scope engagements. You know what you are getting before we start. No retainer, no scope creep, no six-month pilot before you see something working.
Ready to build a voice AI system?
30 minutes. We scope the use case, the call volume, the integration points, and what production looks like. No pitch deck.
