The Enterprise AI Show

The Enterprise AI Show explores the AI journey for Enterprise companies around the world. [formerly The Cloudcast]

As the AI revolution moves from experimentation to execution, The Enterprise AI Show provides the clarity needed to lead. Join Aaron Delp and Brian Gracely as they explore the intersection of generative AI, enterprise systems, and global business strategy. Each episode features clear-headed conversations with the people making actual decisions—founders, investors, and practitioners—focusing on the technical architectures and business models that drive real-world ROI.

New shows every Wednesday and Sunday.

Topics: Enterprise AI strategy · The AI Economy · LLMs in production · AI leadership · Agentic AI · Digital Sovereignty · Machine Learning · AI startups · Cloud Computing

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The Enterprise AI Show

Natural Language Understanding with AI for IT Support

July 15, 2020 • Cloudcast Media

0:00 | 27:59

Vaibhav Nivargi (CTO & Founder @Moveworks) talks about Natural Language Understanding (NLU), interacting with users using chatbots, and augmenting customer service with AI.

SHOW: 458

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SHOW NOTES:

Moveworks Homepage

Topic 1 - Vaibhav, welcome to the show. Tell everyone a little about yourself and what got you started in the AI space?

Topic 2 - We’ve done a number of AI/ML shows over the years, but we haven’t talked much about Natural Language Understanding or NLU. Let’s start there, can you give everyone an introduction?

Topic 3 - Based on that, is the primary interaction with the end user through a chatbot or something similar? What are the primary use cases and tools you are seeing in the industry? Is this a Slack and/or Microsoft Teams integration? Unsolicited plug, I’m a customer in my day job…

Topic 4 - We’ve been talking a lot on the show recently about the migration to SaaS based products. What is the model here? Is the AI central (cloud hosted) or private and in-house? Do you have the concept of a template AI and then each customer AI is an instance or is this a central AI that is called? How does it get customized and updated over time? What training is typically required and is this training on-going?

Topic 5 - How do you prevent user frustration from “loops” or unanswered questions? I think of the voice automated telephone systems I’m not a fan of as an example. How would you handle language that isn’t built into the AI?

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