Play 33
Voice AI Agent
High✅ Ready
Real-time voice AI — speech-to-text, intent recognition, conversational AI, text-to-speech.
Real-time voice-driven AI agent combining speech-to-text, intent recognition, conversational AI processing, and text-to-speech output. Build voice bots for customer service, IVR systems, and accessibility applications. Azure AI Speech handles STT/TTS, Azure OpenAI provides conversational intelligence, Communication Services manages telephony, and Container Apps hosts the streaming pipeline. Supports multi-language, low-latency voice interactions with PII redaction and call recording consent.
Architecture Pattern
Voice pipeline: STT → intent → LLM → TTS, real-time streaming, multi-language
Azure Services
Azure AI Speech (STT + TTS)Azure OpenAI (gpt-4o)Communication ServicesContainer Apps
DevKit (.github Agentic OS)
- agent.md — root orchestrator with builder→reviewer→tuner handoffs
- 3 agents — Voice Builder (gpt-4o), Reviewer (gpt-4o-mini), Tuner (gpt-4o-mini)
- 3 skills — deploy (109 lines), evaluate (107 lines), tune (106 lines)
- 4 prompts — /deploy, /test, /review, /evaluate with agent routing
- .vscode/mcp.json — FrootAI MCP with Speech key + OpenAI key inputs + envFile
TuneKit (AI Config)
- config/openai.json — voice-optimized model params
- config/speech.json — language, speed, voice selection
- config/guardrails.json — PII redaction, consent tracking, profanity filter
- evaluation/eval.py — Voice quality >90%, Intent accuracy >85%
Tuning Parameters
Voice models and languageIntent thresholdsFallback chainsResponse latency targets (<500ms)Speech rate and pitch
Estimated Cost
Dev/Test
$150–350/mo
Production
$2K–8K/mo