Prowler Raises $13M for its New Approach to decision making in AI


One of the persistent and big questions the humanity has been wondering about is the following: will an AI system ever be able to make decisions as well as a human can? With that in mind,, a startup out of Cambridge, is developing a new kind of decision-making platform. It is based on probabilistic modeling, reinforcement learning, and game theory. The startup believes it may help the AI community answer that question with a “yes.”  Moreover, is finally announcing that it has raised $13 million to help it along the way.

If you think about it, artificial intelligence has become an increasingly crowded area. Accordingly, CB Insights estimates that in 2016, 550 startups closed 658 deals, raising $5 billion in funding. If we compare that figure to 2012 we will see that there was a booming 60% increase. Furthermore, larger tech companies like are also doubling down on AI technology. Those include Google, Apple, Amazon, Facebook, Baidu, and Microsoft.

Al is an area that is ready for acquisition. Some of those big tech companies are also snapping up AI startups. They do that in order to pick up new talent and tap into what they’ve built already. Ultimately, there were more than 250 acquisitions of AI-focused startups since 2012, CB Insights notes.

On the other hand, believes it stands apart from the pack. The reason behind is its focus: it is not on perception but on decision making.

“The key thing for us is not what other big AI companies are working on, but what they are not doing,” said CEO Vishal Chatrath, co-founded of the company.

Chatrath also added, that when you look at the “Big 5,” Google, Apple, Amazon, Facebook, and Microsoft, or any company using machine learning, they are focusing on deep neural networks using tens of millions of data points.

“These are fantastic for solving classification and perception problems so that you can say when a dog is a dog. But once you’ve classified the universe you know what’s what. The gap, however, remains decision making,” – Vishal Chatrath

A lot of data

Deep neural networks can be taught decision making of a kind. However, they still rely on a lot of data to train their systems. And that is a problem. “In the real world, you don’t have the luxury of tens of millions of data points. Every choice you make involves micro-decision making in a dynamic environment.”

Prowler is coming at the problem by looking to, and triangulating, learning from math and specifically statistics that it overlays on top of more traditional machine learning.

Moreover, its platform uses probabilistic models “to generalize to novel situations and adapt to changing environments by refining their strategies in data-driven ways”; Reinforcement Learning algorithms that estimate and account for uncertainty; and Game Theory to operate in multi-agent settings to infer what humans and other AIs are trying to do.

Prowler is potentially game changing, but not that fast to build. It still has to launch a commercial product or sign a customer. Although, it has been hiring a lot of impressive academic talent. In any case, there are several potential customers in the pipeline that cannot be disclosed.

Prowler: everything based on word of mouth

“We are in negotiations to close contracts under NDA, and we are finalizing with one in the games industry,” Chatrath said.

Furthermore, a lot of interest came from ridesharing companies and those in finance. Interestingly, every interested company that came to Prowler was based on word of mouth.

Moving on, one thing that Prowler is still working on is the best architecture for its platform. It has two parts: a learning engine and a decision-making engine. In the meantime, the company continues to have the support of its investors. The startup wants to see if it can really help make decisions better than the other solutions for decision making that are out there today.

“ has assembled a world-class team of researchers to tackle some of the most intractable problems of our age. The fact that the company is able to capitalize on the expertise in probabilistic modeling, principled machine learning and game theory available in Cambridge is hugely exciting. The combination of’s team and technology applied to the important problems they are solving provides a significant commercial opportunity for the company.” – Andrew Williamson, Investment Director at Cambridge Innovation Capital

Armen Margarian

Armen Margarian is an attorney with The Margarian Law Firm.

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