KI & AI

AI Voice Assistants for Business: From Idea to Productive Deployment

Kevin KrögerKI & AI

Voice assistants are no longer just consumer products. More businesses are deploying custom AI voice assistants – for customer service, internal processes, and accessibility. This guide shows you how to design, develop, and deploy AI voice assistants for your company.

Use Cases for Business Voice Assistants

Voice assistants offer diverse applications: Customer Service: Phone self-service, FAQ via voice, appointment scheduling. Internal Processes: Meeting transcription, voice-controlled database queries, hands-free work. Accessibility: Voice control for motor impairments, text-to-speech. More on AI in customer service.

Technology Stack

Key technologies: STT: OpenAI Whisper, Google Cloud, Azure. NLU: LLMs, RAG, Rasa. TTS: ElevenLabs, Azure Neural TTS, Google Cloud TTS. At Axis/Port., we develop custom voice assistants with cutting-edge AI.

Development and Training

Phase 1: Design – Define persona, design dialog flow, create intent catalog. Phase 2: Development – Build STT/TTS pipeline, train NLU, implement backend. Phase 3: Testing – Test in various environments, cover edge cases. Phase 4: Deployment – Provision infrastructure, set up monitoring.

Privacy and Ethics

Voice data is particularly sensitive: GDPR: Explicit consent, purpose limitation, define deletion periods, technical measures. Ethics: Transparency, avoid bias, responsible AI. Data Storage: Avoid permanent storage, on-premise if possible, hosting in Germany for compliance.

Fazit

AI voice assistants offer enormous potential for businesses. The technology is mature. At Axis/Port., we develop individual voice solutions.

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