Zohar Bronfman, CEO and Co-Founder PecanDuring his many years of military service in the Israeli army, or while earning two PhDs in computational neuroscience and one in the history of philosophy, he never considered a career in technology. His journey from military to academic to his CEO of his rapidly growing AI/ML tech startup is as extraordinary as it is inspiring.
Pecan is an AI-powered analytics platform that leverages AI and ML to deliver advanced analytics and predictive modeling solutions. It utilizes AI techniques to automate and enhance various aspects of the analytical process, enabling businesses to gain valuable insights and make data-driven decisions without the need for existing data science proficiency. .
I spoke with Zohar about his transition to startup co-founder, how Pecan differs from other analytics providers, and his company’s relationship with Microsoft solutions. But the first question was how to pronounce his company’s name.Pecan,” again “Phae Khan”?
“We have a company motto,” laughs Zohar. “It doesn’t matter how you pronounce it, as long as you buy it.”
Rapid growth by capturing market needs
Zohar was quick to admit that his path to tech startup founder and CEO was unusual. During his three years in the Israeli army, he was assigned to the country’s largest intelligence unit, but in the non-technical sector. His subsequent academic pursuits were also far from a definitive career in AI/ML, but they set the stage for what was to come.
“On the first day of my master’s degree in neuroscience at Tel Aviv University, I met our co-founder and CTO Noam,” recalls Zohar. “We became interested in the fields of machine learning and data science and how models can emulate brain processes to predict human behavior.”
Zohar and Noam then launched Pecan to develop an automated machine learning (autoML) platform designed to be accessible to enterprises without the need for data science or programming expertise. The solution can automatically generate the best possible model for a given problem based on the data provided, making it ideal for companies without a dedicated data science team and for rapidly implementing machine learning models. Especially suitable for companies that need to work.
“Implementing these models is a big problem,” says Zohar. “Too much money is being dumped down the drain due to a lack of capacity to find and train machine learning talent. It speaks of value.
“There are barriers to entry into our space when it comes to competition, especially data automation. You can use our services.”
“Our mission is to put the power of data science in the hands of data and BI analysts,” he continues. “And we recently opened a platform where anyone can sign up to try out our automated predictive analytics.
Innovation in AI and ML
Pecan uses several AI techniques to automate and enhance the analytical process, including data preparation and feature engineering, templating models that address specific business problems, and SQL-driven modeling with autoML. , enabling customers to gain valuable insights and enable data-driven businesses. decision. Zohar said one of the biggest problems Pecan tackles, he said, is how to get the data to build the model properly, other than reducing the need for his scientists to have trained data to implement the model. said to collect.
“In an enterprise, data may not be properly prepared, structured, or designed for machine learning,” explains Zohar. “We took the raw data and built automation around transforming, matching, reconstructing, cleansing and engineering it so that it could be fed into ML algorithms in a meaningful way.”
Zohar said the patented technology opens up a new field of innovation with the potential to meet a wide range of applications such as customer segmentation, churn prediction and personalized marketing. One of Pecan’s goals is to develop models that are not only accurate, but transparent and explainable. Zohar believes this will help differentiate his Pecan in the market as more companies adopt AI and ML.
“There are barriers to entry into our space from a competitive perspective,” Zohar said. “Especially when it comes to data automation. Our main advantage is that our customers don’t need any prior knowledge in this area to use our services, as they don’t require expertise in data science.”
Close partnership with Microsoft paves the way for mentorship
Zohar said another key to Pecan’s market penetration is its close partnership with Microsoft. Through connections with other of his Microsoft clients, Pecan adds the value of his platform to existing Microsoft software and helps them grow their customer base over time.
“We are very proud to work with Microsoft,” says Zohar. “We have had great support, both on the technical side and on the go-to-market side.”
Pecan’s platform is built on Azure data brickadapting the Azure infrastructure, Apache Spark in Azure HDInsight for automation. The company trains and deploys his ML models. Azure machine learningintegrate with Azure data factorywhose data is Azure data lake, it will be possible to store large amounts of data at low cost.In addition, Pecan also integrates with Power BIallowing users to visualize and analyze data.
“Thirty percent of data analysts use Power BI,” explains Zohar. “We are already seeing customers integrate Pecan forecasts into their Power BI dashboards and tools. It includes analyzing and communicating what happens.All in all, these are exciting opportunities to expand the meaning and impact of business analytics.”
Zohar said Pecan’s membership in Microsoft for Startups Founders Hub has also benefited the company.
“We have worked closely with Founders Hub over the years. They have always supported us through content, mentorship and programs to help us grow personally and make connections. “We had a lot of fun,” explains Zohar. “Now that I am asked to coach, I am really proud of the collaboration we have created.”
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