Thought Leaders in Artificial Intelligence: John Price, CEO of Vast (Part 4)

John Price: The other thing we do with the image is, we can determine what’s the make and model of that car just from the image. From there, we can generate all of our analytics about that car. Now you can just take a picture of a car and we can generate a CarStory report for that automobile. >>>

Thought Leaders in Artificial Intelligence: John Price, CEO of Vast (Part 3)

Sramana Mitra: I have a couple of questions. Tell me how you go to market. You mentioned, in passing, that your customers have dealer networks. Explain to me what is the usage model of your product and who’s buying, who’s using, and how.

John Price: Given that it’s a stack, we have users at every layer of our stack. I have customers that just take my aggregated, clean, normalized data and use it. Capital One uses it for their lending process.

Sramana Mitra: For the loan approval process. >>>

Thought Leaders in Artificial Intelligence: John Price, CEO of Vast (Part 2)

John Price: Back to your question, there were no platforms out there to do this with. We had to start with the raw tools that were out there. Then we had to start with the data and focus on our core industry—automotive. The data is a mess. It’s all over the place. It’s very hard to get. When you get it, it’s dirty and incomplete. A lot of times, it’s just flat out wrong.

We spent a decade not only aggregating but also normalizing all that data in all the various data platforms that are out there. We have a very robust ruleset to help complete data where data is incomplete. We’ve had to develop a lot of AI-based image >>>

Thought Leaders in Artificial Intelligence: John Price, CEO of Vast (Part 1)

John is an AI industry veteran, and has both exciting new trends to share, as well as cautionary guidance to offer.

Sramana Mitra: Let’s start by introducing our audience to Vast and yourself.

John Price: I’m the CEO of Vast. We’re headquartered in Austin, Texas. We’ve been around for over 10 years. The company was founded in San Francisco by Naval Ravikant and Kevin Laws with first round funding from Clearstone and Leapfrog Ventures. I joined the company in 2007 and moved the company to Austin around 2010. We’ve been building out Big Data applications for automotive and real estate ever since. >>>

Thought Leaders in Artificial Intelligence: Shan Haq, Vice President of Strategy and Business Development of Transcepta (Part 3)

Sramana Mitra: What is the problem? What can you not do today in that scenario that you would like to do? What is the fantasy there?

Shan Haq: We’ve got some baby steps in this direction, but I think there’s a better way to go. We have a solution around dynamic discounting. This is the idea that an invoice is sent to a customer. On an invoice by invoice basis, a customer can make an offer to the supplier that says, “I’ll pay you more quickly if you give me a discount.”

We take this historical 2% NET10 scenario and make it much more dynamic, and instead of having it be ubiquitous across every supplier, supplier can make the decision on whether or not to accept the offer on an invoice-by-invoice basis. That’s in place >>>

Thought Leaders in Artificial Intelligence: Shan Haq, Vice President of Strategy and Business Development of Transcepta (Part 2)

Sramana Mitra: What is an example of what you’re trying to do with images? What specifically are you trying to achieve with these images?

Shan Haq: One of the things that is important to our customers is the ability to bring a supplier onto our network very quickly. The most common scenario there is being able to take an invoice format from a supplier and turn it into the appropriate invoice format for our customer.

One of the things that we need to do is build that business rule around the invoice. If we can get the invoice from a supplier and very quickly identify, just from the image, that that invoice is coming from a Quickbooks system for example, we can put it into a >>>

Thought Leaders in Artificial Intelligence: Shan Haq, Vice President of Strategy and Business Development of Transcepta (Part 1)

The procure-to-pay space is going through huge technology adoption, and AI is making its mark on it as well. This interview explores the nuances of the sector.

Sramana Mitra: Let’s start by having you introduce yourself as well as Transcepta to our audience.

Shan Haq: I run Corporate Strategy and Development for Transcepta. My background is mostly in product management and marketing. I have previous experience with Microsoft, Deloitte, and Boeing. I started with Transcepta just a couple of months >>>

Thought Leaders in Artificial Intelligence: Gurjeet Singh, Co-Founder and Chairman of Ayasdi (Part 5)

Sramana Mitra: Do you want to talk about the healthcare use case a bit?

Gurjeet Singh: Similar to financial services, we build applications that solve problems end-to-end. The first application in healthcare that we sell to both healthcare payers and providers is the application that detects and hopes to mitigate the problem of clinical radiation.

Given the regulatory environment in healthcare and the way it’s changed over the past two years, one of the major problems is that healthcare providers in particular are beginning to have to own risk for their populations. Medicare essentially pays what’s known as a bundle payment. Think of it as I’m going to give you >>>