Voice AI Development
Voice agents and speech features that handle real conversations, not just scripted prompts.
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Voice AI development is building applications that understand and respond to spoken language — voice agents for customer support, IVR replacement, transcription, and hands-free workflows — combining speech-to-text, an LLM for understanding and response, and text-to-speech, often in real time. DuCodes builds these pipelines with the same escalation and fallback discipline we apply to text-based AI features.
Voice adds real constraints text-based AI doesn't have: responses need to happen in near real time, speech recognition needs to handle accents and background noise, and a voice agent that gets confused mid-call needs a graceful way to hand off to a human, not a dead silence. We build voice AI features — call-handling agents, voice-driven internal tools, transcription and summarization pipelines — around those constraints specifically.
This typically combines a speech-to-text layer, an LLM handling understanding and response generation, and text-to-speech for the reply, wired together with the latency budget a real conversation actually requires.
Why work with DuCodes on this
Designed for real-time constraints
Latency budgets for a natural-feeling conversation are part of the architecture decision from the start, not discovered after the demo feels sluggish.
Graceful human handoff
A voice agent that's uncertain or stuck gets a defined path to transfer to a person, the same discipline we apply to chat-based agents.
Built for real speech, not clean demo audio
Accents, background noise, and interruptions get accounted for in testing, not just clear studio-quality sample audio.
Integrated with your existing phone/support stack
Voice agents connect into your actual telephony or support system rather than existing as a standalone demo.
How we work
Scope the conversation
What the voice agent should handle end-to-end, and where it needs to hand off to a human.
Choose the speech stack
Speech-to-text and text-to-speech providers selected for your language, accent, and latency requirements.
Build the conversation logic
LLM-driven understanding and response, tuned against real (or realistic) call transcripts.
Test with real audio conditions
Background noise, accents, and interruptions tested explicitly, not just clean sample recordings.
Deploy & monitor call quality
Ongoing review of real call transcripts to catch misunderstandings and tune the system after launch.
Technology we use
Frequently asked questions
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