Nuance Partner eXperience Summit Review: An accelerated transformation in a fluid market

by | Mar 2, 2020 | Blog, Content, IVR

Since Mark Benjamin joined Nuance as its new CEO almost two years ago, the company has been going through a breathtaking transformation. After selling its imaging division to Kofax and spinning off its automotive division, the company now focuses primarily on its core business of providing conversational AI products and solutions.

Even in its core conversational AI business, Nuance is fast transforming itself from a software company with a very large focus on professional services to a product and platform company. This was evident at the 2019 Partner eXperience Summit, but it was even more so at this year’s event.

This change was of course necessary and, I might add, a bit overdue. Long the dominant vendor of enterprise speech technology solutions, Nuance is now being challenged by companies – Google, Amazon, Microsoft, and IBM among others – that offer easy to use conversational AI platforms with state-of-the-art technologies. With these platforms, the claim is that anybody can now develop sophisticated conversational AI solutions; that speech recognition (ASR) and natural language understanding (NLU) work “out-of-the-box” without any need for speech scientists; and that, in fact, you don’t even need developers to build solutions. This is the “do-it-yourself” (DIY) message and it is a compelling one.

Of course, that message is highly misleading. Yes, to some extent, the technology now works “out-of-the-box” in the sense that it is possible to get a simple conversational demo bot up-and-running quickly. With speech-to-text (STT) engines, there is no need to write speech recognition grammars and NLU engines can be trained with a few training phrases per intent. But that’s only good for a demo. Building an effective, enterprise-grade conversational AI system is hard work, no matter what the platform is (more on that in a future blog post).

What is true, though, is that enterprises really are looking for DIY tools. And they are increasingly demanding cloud-native solutions. And, above all, they want flexibility. And Nuance has heard that message loud and clear. They now understand that it’s no longer sufficient to have best-in-class technology and a good professional services organization. Customers want to have flexible development and deployment models.

The most recent big steps that Nuance has taken in that direction are:

  • Conversational AI APIs (launched November 2019);
  • The Nuance GateKeeper cloud based security and biometrics suite (launched October 2019);
  • Nuance Mix: DIY Tooling for partners and end users (general availability planned for end of March)

The introduction of Nuance Mix, in particular, is a big change for a company that is used to directly delivering most of its conversational AI solutions through its professional services organization, using closely guarded development tools. But what we’ve seen so far of Mix is promising, with a slick, contemporary user interface. From a company that has years of experience building and deploying compelling conversational AI solutions, this is quite encouraging.

Nuance is facing powerful new competitors, but it has many advantages. Its technology is top-notch, it has a very large installed base, it offers the most flexible deployment models (premise or cloud), its technology is integrated with most contact center platforms, and it understands better than anybody what it takes to deliver conversational experiences that work not just in demos, but in the real world. Nuance also offers the most extensive capabilities to adapt and optimize the technology for a specific domain and a specific dialog state, which is often what makes the difference between a good demo and an enterprise-grade solution.

Another Nuance differentiator – which they position as a key element of their value proposition – is its strong professional services organization. But that could also turn out to be its Achilles’ heel, because customers no longer want to be dependent on the vendor’s PS; they want to know that there is a large pool of people that are skilled on the technology and have all the tools necessary. It will be a challenge to change a company that is culturally used to delivering all the big projects into one that enables its partners and customers to do it themselves.

In conclusion, Nuance is clearly going in the right direction and making all the right moves, but its plan is ambitious, so execution will be key. Perhaps the biggest challenge will be to implement the culture changes that are required in order to successfully implement this transformation.

We’ve been in this market for close to 20 years and these are by far the most interesting times we’ve seen. We’re expecting quite a ride in the next few years.

About the author: <a href="" target="_self">Yves Normandin</a>

About the author: Yves Normandin

A leading authority in speech recognition, natural language processing and machine learning, Yves brings over 30 years of experience to the team. His career has included research, product and application development, and business development. Today, he’s responsible for defining the corporate direction and technological vision of Nu Echo, as well as leading our speech platform and building strategic alliances.
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