Thought Leaders in Artificial Intelligence: Daisy Intelligence CEO Gary Saarenvirta (Part 1)

Gary is implementing AI concepts from his Aerospace industry background onto use cases in retail and insurance.

Sramana Mitra: Let’s start by introducing you and Daisy Intelligence. 

Gary Saarenvirta: I’m the Founder and CEO of Daisy Intelligence. Daisy Intelligence is an AI platform. We help our clients make smarter operating decisions. Our mission is to empower human beings to do what humans are very good at by letting machines do what machines are good at.

We have a couple of uses cases we address today in retail. It’s a large segment of our business. We help retailers make smarter merchandise planning decisions. We help them to decide what products to promote, what prices to charge, and how much inventory to allocate.

Our system delivers the decision. It’s an autonomous decision-making system with no human in the loop. We deliver the answer to our clients. In the long run, our mission is to change the role of the human and let the machines do some of these beyond-human capability decisions.

We also work in insurance. We do fraud detection and underwriting where we help insurance companies identify which claims are fraudulent, which people are committing fraud, and what organized networks are getting fraudulent activity. We can underwrite new business, identify the risk, and recommend pricing.

We deliver a decision. Our users execute on the finding. There is no human in the loop, so we are a product company. We are SaaS. We charge a monthly subscription. We have been delivering massive financial returns. In retail, we are able to grow total company sales by more than 5%.

Sramana Mitra: Let’s do some use cases. What are the customer segments that you are going after? Retail seems to be one of them.

Gary Saarenvirta: Retail and insurance are the two top segments. We have 20 retailers in five countries. It’s focused on merchandise planning. Every single week, retailers decide what products to promote. That’s beyond human capability.

End consumers don’t buy a product; they buy solutions or use cases. A product like ground beef is just one product. The use case is an Italian dinner. You can buy ground beef, pasta, tomato sauce, or cheese. If you’re making hamburgers, you need ground beef, buns, condiments.

Contrast that to a product like water. You don’t need other products to consume water. If you promote a product with a larger use case, you’ll drive larger transactions.

We net out all the ripple effects. Since you bought ground beef to make hamburgers, hotdog sales go down. Since hamburger buns were purchased, hotdog buns sales go down. As the product was on sale, the customer bought a four-week supply. We measure all these positive and negative effects.

Sramana Mitra: What are the users of this analysis? Is it marketing or is it merchandising?

Gary Saarenvirta: Merchandising. We deliver the answer. We just say, “In your flyer, put milk, bread, and eggs. On the website, put water and chips.” We give them the answer. They can then edit our recommendation or execute them.

In the long run, this will be like the stock market. Human traders don’t exist to the same degree they did 20 years ago. It’s computer trading with human oversight. We believe that in merchandising, it will be computer merchandising with human oversight.

This segment is part 1 in the series : Thought Leaders in Artificial Intelligence: Daisy Intelligence CEO Gary Saarenvirta
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