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Zohar Bronfman, CEO and Co-founder of Pecan, had no inkling of a profession in tech throughout his years of army service within the Israeli military, or whereas incomes two PhDs in computational neuroscience and one other within the historical past of philosophy. His journey from soldier to scholar to CEO of a quickly rising AI/ML tech startup is as uncommon as it’s inspiring.
Pecan is an AI-powered analytics platform that leverages AI and ML to offer superior analytics and predictive modeling options. It makes use of AI methods to automate and improve numerous elements of the analytics course of, enabling companies to realize useful insights and make data-driven selections with out a want for current knowledge science proficiency.
I sat down with Zohar to speak about his transition to startup co-founder, what differentiates Pecan from different analytics suppliers, and his firm’s relationship with Microsoft options. The primary query, nevertheless, was the right way to pronounce his firm’s identify: “PE-can,” or “peh-CAHN”?
“We’ve an organization motto,” Zohar laughs. “It doesn’t matter the way you pronounce it, so long as you purchase it.”
Speedy progress introduced on by recognizing a market want
Zohar is fast to confess that his path to tech startup founder and CEO is atypical. Throughout his three years within the Israeli military, he was stationed within the nation’s largest intelligence unit however assigned to the non-technological division. His subsequent educational pursuits have been additionally removed from his eventual profession in AI/ML, however they set the stage for what was to return.
“I met Noam, our cofounder and CTO, on the very first day of our Masters in Neuroscience in Tel Aviv College,” Zohar remembers. “We got interested within the subject of machine studying and knowledge science and the way fashions can emulate mind processes and predict human conduct.”
Zohar and Noam would then launch Pecan and develop its automated machine studying (autoML) platform, designed to be accessible to companies with out requiring experience in knowledge science or programming. Able to robotically producing the very best mannequin for a given drawback based mostly on the information supplied, the answer is especially well-suited for companies that don’t have devoted knowledge science groups or that want to maneuver shortly to implement machine studying fashions.
“Implementing these fashions is a large drawback,” Zohar says. “A ton of cash is thrown down the drain due to a scarcity of capability to search out and practice machine studying expertise. Our speedy progress speaks to the necessity out there and the worth potential prospects see in our platform.
“There are obstacles to coming into our area by way of competitors, particularly regarding knowledge automation. Our important benefit is that our prospects don’t require experience in knowledge science, which is enabling them to make use of our providers with none prior information within the subject.”
“Our mission is to place the ability of knowledge science within the fingers of knowledge and BI analysts,” he continues, “and we’ve just lately opened our platform for anybody to enroll and check out their hand at automated predictive analytics. We’re excited to see increasingly more knowledge analysts tackle predictive modeling and assist drive enterprise success.”
Innovating within the subject of AI and ML
Pecan’s use of a number of AI methods to automate and improve their analytics course of—together with knowledge prep and have engineering, templates for fashions that deal with particular enterprise issues, and SQL-driven modeling with autoML—permits their prospects to realize useful insights and make data-driven selections. Zohar says one of many largest issues Pecan addresses, apart from lowering the necessity for educated knowledge scientists to implement fashions, is correctly gathering knowledge with which to construct fashions.
“An organization could not have knowledge correctly ready, structured, or engineered for machine studying,” Zohar explains. “We constructed automation round taking uncooked knowledge and reworking, collating, restructuring, cleaning, and engineering it so it may be meaningfully fed into the ML algorithms.”
Zohar says this patented know-how opens a brand new subject of innovation with the potential to fill a wide selection of purposes, together with buyer segmentation, churn prediction, and customized advertising. One in every of Pecan’s targets is to develop fashions that aren’t solely correct but in addition clear and explainable. Zohar believes this may assist differentiate Pecan out there as extra companies undertake AI and ML.
“There are obstacles to coming into our area by way of competitors,” Zohar says, “particularly regarding knowledge automation. Our important benefit is that our prospects don’t require experience in knowledge science, which is enabling them to make use of our providers with none prior information within the subject.”
An in depth partnership with Microsoft forges a path to mentorship
Zohar says one other key to Pecan’s market penetration is their shut partnership with Microsoft. By their connections with different Microsoft purchasers, Pecan can add the worth of their platform to current Microsoft software program, serving to them to step by step develop their buyer base.
“We’re extraordinarily proud about working with Microsoft,” Zohar says. “We get wonderful assist on each the technological and go-to-market sides.”
Pecan’s platform is constructed on Azure Databricks, adapts an Azure infrastructure and makes use of Apache Spark in in Azure HDInsight for automation. The corporate trains and deploys its ML fashions on Azure Machine Studying, integrates with Azure Knowledge Manufacturing unit, and homes its knowledge on Azure Knowledge Lake, permitting them to retailer giant quantities of knowledge at a low price. As well as, Pecan additionally integrates with Energy BI, permitting their customers to visualise and analyze their knowledge.
“Thirty % of knowledge analysts use Energy BI,” Zohar explains. “We already see our prospects integrating predictions from Pecan into their Energy BI dashboards and instruments. BI now contains greater than analyzing what occurred up to now—it’s additionally analyzing and speaking what’s going to occur sooner or later. Throughout the board, these are thrilling alternatives to develop the that means and impression of enterprise analytics.”
Zohar says Pecan’s membership within the Microsoft for Startups Founders Hub has additionally paid dividends for the corporate.
“We’ve been working intently with the Founders Hub for years, they usually have all the time been there for us with content material, mentorship, and packages which have helped us develop individually and make connections,” Zohar explains. “It’s reached the purpose the place now I’m being requested to offer mentorship, so I’m actually pleased with the collaboration we’ve generated.”
Microsoft for Startups Founders Hub members obtain Azure cloud credit that can be utilized towards Azure OpenAI Service or OpenAI to assist construct their product. Enroll now to change into a member.
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