Almost suddenly, it seems, the marketplace has become full of companies – both large players and small insurtechs -- that provide high-tech property risk analytics for insurance in one form or another. Marsh, CyberCube, Guidewire, CoreLogic, Willis Towers Watson and Arturo are among the many competitors.
And then there’s Zesty.ai. The California-based company recently raised $33 million to fuel, in part, a major product expansion. Zesty.ai founder and CEO Attila Toth (pictured) acknowledged the competitive dynamic, but he insists Zesty is one company in the space that is most definitely sticking around.
“We are building this company because we are enjoying the process and because we want to have an impact on this industry,” Toth said. “We are not building this company for a quick sale.”
Tech driven, sane growth
Zesty.ai initially debuted in 2016 and started its first foray into the insurance space in 2018. The company employs just under 60 people and is hiring aggressively, with expectations that a good 25% of its workforce will be new within the next few months.
Zesty.ai’s recent $33 million Series B round, led by Centana Growth Partners, is designed to help the company expand its insurance products but also grow into the real estate market, which has similar property assessment needs. Plans also call for using the money to build up the brand.
“We will be investing heavily into sales and marketing [and] hiring additional salespeople,” Toth said, with potential marketing areas including thought leadership, content and channel partnerships.
Overall, the company has raised a little under $50 million in venture capital financing to date.
Zesty.ai uses data sources including satellite imagery, weather data and artificial intelligence to build predictive models that can better explain the impact of natural disasters such as wildfires, hurricanes, floods and more on homes and businesses. Aerial imagery from low-flying aircraft can also be part of the equation.
Zesty.ai’s technology ingests that basic data, using artificial intelligence (AI) including computer vision to turn it into models that users can comprehend. There is also the use of convolutional neuro networks to analyze visual imagery. Zesty.ai builds its detailed risk models from its various data sources.
“We have a wildfire risk product which is accurately predicting the likelihood of an address falling within a wildfire event and then also accurately predicts [exposure] within that event – [and] how [much] damage you should expect,” Toth explained.
Broadly speaking, Zesty.ai builds a digital twin of every building in North America, encompassing 200 billion property insights accounting for all details that impact a property’s value and associated risks.
Toth describes Zesty.ai’s technology in operation as a “multi-layered architecture.”
Customer base and competition
Property insurance companies are Zesty.ai’s primary customer base, and they use its technology to be able to better underwrite and rate property risks. Zesty.ai said it partners with about half of the top 50 property/casualty insurance carriers in the US - Amica, Aon, Berkshire Hathaway, Cincinnati Insurance, Farmers Insurance and The California FAIR Plan are among the company’s customers. Smaller regional carriers and MGAs are also part of Zesty.ai’s customer base.
The company is not profitable yet but Toth insists it is close.
“We are not profitable by choice because we are investing a lot into our growth,” he said. “We could be profitable if we dialed back on growth, but given the fact that even in tough markets, we have access to capital markets, we will be very prudent in how we deploy this capital.”
Toth added that Zesty.ai is “not the drunken sailor-type of Silicon Valley company,” even with the new venture capital financing round.
“We will be extremely prudent in terms of how we will be investing this money and we will always maintain our position close to profitability while we’re investing to grow,” he said.
That will even be in the case of sizeable competition, Toth said, some of whom he expects to consolidate or go-out of business in following “the normal course of evolution of startup companies.” The investment climate has become substantially tougher, and Toth suggested that dynamic may even accelerate the departure of some rivals.
“You will … see some companies going out of business because raising money under this new environment is going to become more difficult,” Toth said. “If you are not close to profitability, if you don’t have a good business model, if you don’t have good unit economics and if you don’t have customers that are raving about you, raising money is going to be increasingly difficult over the next couple of years.”