5 Reasons Amazon and Google are Losing Customers to Deepgram

Amazon and Google are often people's first thought when it comes to speech recognition systems, but if you've ever tried to use these ASR tools, you know that the big name doesn't help you get accurate, timely results. In fact, people's first encounter with Big Tech speech recognition often leaves them wanting more, and sends them searching for a better solution to power their voice-driven future. According to an upcoming survey conducted by Opus Research, only 1% of respondents didn't think that voice-enabled experiences were going to be a critical part of their company's future enterprise strategy. That means that you need fast, accurate ASR that's easy to use if you're going to keep pace with your peers and competitors.

So what are five of the top reasons that companies are switching from Big Tech to Deepgram for their automated speech recognition needs? And why are they delighted with Deepgram when they've made the switch? Let's take a look.

Real talk: Amazon and Google are slow. Their legacy way of doing speech recognition means that incoming audio has to go through multiple stages during processing, which in turn means that any real-time applications like interactive chatbots or truly real-time captioning is out of the question. Deepgram's end-to-end, hardware-accelerated deep learning ASR system, on the other hand, returns results in a fraction of the time-up to 60x faster than Big Tech-even while processing multiple audio streams.

Most speech recognition systems are "good enough"-you can listen to some audio, look at a transcript of it, and figure out how the ASR system got from A to B. But if you've ever used a device or product from Big Tech that relies on speech recognition to turn on your lights or get directions, you know that good enough often isn't actually good enough. For critical business functions like customer service, sales, and operations, you can end up giving yourself more work instead of less if you're constantly fighting with crummy transcripts. Deepgram's ASR system consistently outperforms Amazon, Google, and other Big Tech providers out of the box (all while also being faster, as noted above).

But what if that out-of-the-box accuracy isn't good enough? What if it's still driving extra work while you try to figure out what to do with confusing transcriptions? If you're working with Big Tech, you're out of luck; the out-of-the-box accuracy is the only accuracy. But with Deepgram, you can quickly and easily train a tailored model that understands the words you need it to, driving gains and accuracy and thus ROI. Have jargon-filled phone calls about widget manufacturing processes? No problem, we can tailor a model that knows those words as well as it does the rest of the English (or any of the other languages we offer).

If you encounter a problem while using one of Big Tech's solutions, hopefully it's something that's addressed by the documentation or by another user on Stack Overflow. If not, you'll quickly discover it's all but impossible to get any kind of customer support. Not so with Deepgram-we want you to succeed, not just toss your money at us and make your API calls. We've got a full-fledged set of developer tools and a developer community to help you get the most out of your voice technology implementations. We also have live, expert humans who can help you optimize your voice technology. Developers have said that signing up and connecting to our APIs was the fastest and easiest process they've ever used.

Did you know that both Amazon and Google charge in 15 second increments for their speech-to-text services? That might not sound like a big deal, but if you're processing a lot of audio-especially a lot of short requests-you're going to end up paying for a lot of time that you didn't even use. At Deepgram, we charge you for the length of your audio.You only pay for what you use, with no rounding up to pad our pockets.