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5 Ways to Reduce Voice AI Costs Without Losing Quality

1. Cache Your Synthesized Audio One of the biggest drivers of cost in voice AI is the sheer number of API calls you make to a TTS provider.

  • Cache synthesized audio to avoid repeated API charges
  • Batch requests and use parallelism to reduce overhead
  • Optimize text length and pacing to cut audio costs

Introducing Anthropic models on Amazon Bedrock for in-region inference in Seoul and Singapore

Amazon Bedrock now supports Anthropic's Claude Opus 5 and Claude Sonnet 5 with in-region inference in Seoul, and Claude Sonnet 5 in Singapore.

  • Anthropic Claude Opus 5 and Sonnet 5 models available in Seoul and Singapore
  • Inference processed entirely within AWS regions, meeting data residency needs
  • Access models via bedrock-runtime endpoint with Messages, InvokeModel, and Converse APIs

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