Daisy Intelligence CEO Gary Saarenvirta thinks businesses can gain by using more math and science to make decisions.SUPPLIED
Gary Saarenvirta chose the name Daisy Intelligence for the firm because Daisy was the first song ever sung by a computer and the number of petals in a daisy are a Fibonacci number.
Daisy deploys a type of artificial intelligence (AI) called reinforcement learning to help guide clients in the retail and insurance sectors to make business decisions.
The results for clients is impressive.
“We help our clients, whose revenue ranges from $100 million to over $30 billion to increase their top line sales by an average of 3 % to 5%. That’s a huge increase in retail where margins are 1% and less.” Saarenvirta says.
With its own revenue reaching $5-million last year, Daisy and its team of more than 50 computational scientists, mathematicians and retail experts in Toronto, Ont, has seen revenue grow by more than 1,300 per cent.
“We want to keep doubling in revenues for the next three or four years,” Saarenvirta says. Daisy’s growth coincides with the rapid rise of AI as a force in the business world, as machine learning becomes more sophisticated.
The difference between Daisy and other AI companies is that “to my knowledge, we’re the only supplier of this particular type of AI [Daisy’s own patent-pending type of reinforcement learning] to the commercial world,” he says.
“It’s a technology that delivers decisions,” he explains. Just as the AI used in a self-driving car simulates billions of alternative of driving decisions to find the optimal driver inputs to keep the car on the road and manoeuvring safely, reinforcement learning looks at all the factors that affect business transactions, to make the optimal decisions that drive business growth.
“For example, for our insurance clients, Daisy can look at all the details of a particular insurance claim and detect fraud in ways that humans cannot see.” he says.
The company helps insurance companies detect fraud at every stage in the claims process by augmenting traditional business rules, watching lists, and tip lines with powerful systems to discover collusion, non-obvious relationships, and outliers.
Saarenvirta says that Daisy is sensitive to the challenges its clients face too, as they use more and more AI and workplaces are disrupted.
“Senior executives see the value of what we do but many people still have trouble believing what AI can do. Integrating AI with people is a big challenge but becoming easier as business see the great value AI is providing,” he says.
Daisy has a rapidly growing list of clients in five countries (including Canada). It’s very focused on retail and insurance presently but may consider adding other industries in the long term.
He is relentlessly ambitious. “Our long-term goal is to be the next Google or Apple. My dream is that our brand will outlive me – that would mean we have changed the world,” he says.
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