André Woodley Jr.

founder. engineer. creative.

Are Voice AI Platforms a Race to the Bottom?

The Voice AI landscape is rapidly evolving, with numerous platforms offering developers pipelines for integrating voice, large language models (LLMs), speech recognition, and transcription capabilities. The convenience of ready-made pipelines is undeniable, however a concerning trend is emerging – a race to the bottom driven solely by pricing.

I recently consulted a team that seamlessly migrated their infrastructure from one voice AI platform to another within a mere 1-2 days, motivated by better pricing and experience. A week later they stated they would build their own starting with the lower hanging fruit again to lower prices (volume pricing wasn't enough). This eye-opening experience underscores the commoditization of these platforms, where the overall experience is largely similar, and pricing becomes the primary differentiator.

This raises the question: Is this a race to the bottom? If so, should voice AI platforms start by undercutting the market with competitive pricing, and then focus on expanding their offerings and identifying innovative monetization strategies? 

Another problem I see with most voice ai pipeline platforms is the "one-size fits all approach," and lack of customizations. As a result anyone in the Voice AI space may leverage the pipelines to prove value propositions but leave long term. For example - majority of tools only allow one large prompt. This creates an issue because the one prompt is responsible for many pieces which creates bugs and overemphasizes prompt engineering and large prompts which is horrible. Rather mini prompts can be issued and dynamically changed building a more customizable solution built from scratch but no one is offering this right now.

However, initially winning over users through competitive pricing, these platforms could amassing a substantial user base and gain valuable insights into real-world use cases, enabling them to develop more tailored functionalities and better products. Also, voice AI platforms could position themselves as prime acquisition targets for enterprises seeking to bolster their developer ecosystems. Rather than engaging in short-sighted price gouging, a more sustainable approach would be to leverage the volume of users to explore creative monetization models and continuously refine their products based on user feedback and emerging trends.

These are just high-level thoughts.