Don't Price Voice AI at Today's Volume: How to Model Cost at Scale
Blog post from Deepgram
In the article, Jose Nicholas Francisco explores the complexities of pricing models for voice AI systems, emphasizing the importance of accurately projecting costs as usage scales from pilot to production. He highlights that pilot bills can be misleading, as they often fail to account for the increased scale and complexity of production traffic. The article outlines various pricing models, including per-minute, per-character, concurrency-based, and committed tier pricing, each with distinct scaling behaviors and cost implications. Francisco stresses the significance of understanding the interplay between usage units, concurrency, growth rate, and model choice to predict costs effectively. He provides a framework for modeling these factors, using hypothetical scenarios to illustrate how different pricing strategies affect the total costs under varying conditions. The discussion includes considerations on concurrency limits and over-limit behaviors, offering guidance on selecting the most suitable pricing model based on projected traffic patterns and growth assumptions.
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