Voice AI Architecture Guide: When to Choose Modular (Sandwich) Architecture

Use Cases Favoring Modularity

Multi-language deployments:

  • Use Whisper for non-English (superior multilingual)
  • Use Deepgram for English (faster)
  • Route based on detected language

Cost optimization critical:

  • Use GPT-3.5 for simple queries (cheap)
  • Use GPT-4 for complex queries (capable)
  • Route based on intent complexity

Quality differentiation needed:

  • Use ElevenLabs voice for premium customers
  • Use OpenAI TTS for standard customers
  • Route based on customer tier

Rapid provider innovation:

  • New STT provider launches with better accuracy
  • Switch providers through configuration change
  • No architecture overhaul required

Scenarios Requiring Fine Control

Compliance and auditing:

  • Separate STT transcription for compliance recording
  • Separate LLM prompts for different use cases
  • Granular logging per component

Performance optimization:

  • A/B test different provider combinations
  • Optimize each layer independently
  • Measure latency contribution per component

Custom model training:

  • Train custom STT model on industry vocabulary
  • Fine-tune LLM on company data
  • Clone voice for brand consistency