Bringing Google Dialogflow to the Enterprise

Google Dialogflow is a leading conversational AI platform that can be used to build engaging voice and text-based conversational interfaces over any channel, including IVR. Google Dialogflow incorporates Google’s machine learning expertise and products such as Google Cloud Speech-to-Text. Because Google Dialogflow is a Google service that runs on Google Cloud Platform, it lets you scale to hundreds of millions of users.

Why work with Nu Echo on your Google Dialogflow project?

17 years of conversational expertise

Conversational user experience design is about how to ask questions to get predictable responses; how to handle user digressions, corrections, changes of mind; how to manage NLU confidence scores; how to recover from an ASR or NLU failure; how to lead the conversation to maximize success while giving users a sense of control. It is both art and science. But it’s certainly not the kind of expertise that can be improvised. It’s built on years of experience developing best practices and learning what works and what doesn’t.

We were doing conversational user experience design long before people even knew it existed. We have built our conversational practice over the past 17 years so that you don’t have to repeat the mistakes of others.

Proven engineering practices

No matter what development tools you use, an intelligent virtual agent is a complex application that needs to be developed with solid engineering practices that enable you to frequently release new versions that are always bug-free and perform flawlessly.

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Google Dialogflow tooling

Developing simple conversational applications using Google Dialogflow’s web-based tools is easy, but it doesn’t scale to larger projects requiring a development team that follows proven engineering practices. That’s why we build a set of tools needed to support our engineering practices, including:

  • Agent modeling validation and integrity check around intents, entities, follow-ups and responses.
  • Regression testing facilities to confirm that any recent changes have not adversely affected existing features.
  • Continuous integration and delivery following blue-green deployment that reduces downtime and risk by running two identical production environments. At any time, only one of the environments is live, with the live environment serving all production traffic, while the other is serving UAT traffic.

NLU optimization expertise: Because accuracy matters

No matter how good a conversational design is, if NLU accuracy is not there, the entire virtual agent project will end up in failure. For the past 17 years, we have been refining our NLU optimization methodologies and tools to ensure that our conversational solutions deliver the best possible accuracy, success rate, and user experience.

In fact, that’s what we are best known for. Companies across North America come to us simply to improve NLU and ASR accuracy of their current conversational applications.

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