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 supply superior analytics and predictive modeling options. It makes use of AI strategies to automate and improve numerous facets of the analytics course of, enabling companies to achieve worthwhile insights and make data-driven selections with out a want for present information 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 tips on how to pronounce his firm’s title: “PE-can,” or “peh-CAHN”?
“Now we have an organization motto,” Zohar laughs. “It doesn’t matter the way you pronounce it, so long as you purchase it.”
Fast development 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 tutorial pursuits had 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 discipline of machine studying and information science and the way fashions can emulate mind processes and predict human habits.”
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 information science or programming. Able to routinely producing the absolute best mannequin for a given drawback based mostly on the info supplied, the answer is especially well-suited for companies that don’t have devoted information science groups or that want to maneuver rapidly 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 seek out and prepare machine studying expertise. Our fast development speaks to the necessity available in the market and the worth potential clients see in our platform.
“There are obstacles to coming into our area by way of competitors, particularly regarding information automation. Our principal benefit is that our clients don’t require experience in information science, which is enabling them to make use of our providers with none prior information within the discipline.”
“Our mission is to place the facility of knowledge science within the palms of knowledge and BI analysts,” he continues, “and we’ve not too long ago opened our platform for anybody to enroll and take a look at their hand at automated predictive analytics. We’re excited to see increasingly more information analysts tackle predictive modeling and assist drive enterprise success.”
Innovating within the discipline of AI and ML
Pecan’s use of a number of AI strategies to automate and improve their analytics course of—together with information prep and have engineering, templates for fashions that handle particular enterprise issues, and SQL-driven modeling with autoML—permits their clients to achieve worthwhile insights and make data-driven selections. Zohar says one of many largest issues Pecan addresses, aside from lowering the necessity for educated information scientists to implement fashions, is correctly gathering information with which to construct fashions.
“An organization might not have information correctly ready, structured, or engineered for machine studying,” Zohar explains. “We constructed automation round taking uncooked information 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 discipline of innovation with the potential to fill a wide selection of functions, together with buyer segmentation, churn prediction, and customized advertising and marketing. One in all Pecan’s targets is to develop fashions that aren’t solely correct but additionally clear and explainable. Zohar believes this may assist differentiate Pecan available in the market as extra companies undertake AI and ML.
“There are obstacles to coming into our area by way of competitors,” Zohar says, “particularly regarding information automation. Our principal benefit is that our clients don’t require experience in information science, which is enabling them to make use of our providers with none prior information within the discipline.”
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. Via their connections with different Microsoft purchasers, Pecan can add the worth of their platform to present Microsoft software program, serving to them to regularly increase their buyer base.
“We’re extraordinarily proud about working with Microsoft,” Zohar says. “We get superb help 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 Learning, integrates with Azure Data Factory, and homes its information on Azure Data Lake, permitting them to retailer massive quantities of knowledge at a low value. As well as, Pecan additionally integrates with Power BI, permitting their customers to visualise and analyze their information.
“Thirty p.c of knowledge analysts use Energy BI,” Zohar explains. “We already see our clients integrating predictions from Pecan into their Energy BI dashboards and instruments. BI now consists of 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 increase the which means and influence 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 at all times 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 supply 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. Sign up now to become a member.
