Pecan

Pecan AI, founded in Tel Aviv in 2018, offers a predictive analytics platform designed to make machine learning accessible to business intelligence (BI) analysts and business teams without requiring data scientists. The company was established by CEO Dr. Zohar Bronfman and CTO Dr. Noam Brezis, who met during their PhD studies in computational neuroscience and cognitive sciences at Tel Aviv University. Their academic research into brain processes using machine learning sparked the idea to develop a SaaS platform that empowers SQL-oriented analysts with full data science capabilities. The concept for Pecan originated when the founders built a prototype to automate data preparation for a data science competition.

The company's core offering is a low-code platform that automates the entire predictive analytics workflow, from data preparation to model deployment. It allows users to connect directly to raw, messy data sources, and the platform automatically handles cleaning, feature engineering, and model training using neural networks. This significantly reduces the time to generate insights, with models becoming operational in days rather than months. Pecan's key innovation is its "Predictive GenAI," which combines generative AI with predictive AI. This feature includes a "Predictive Chat" that guides users through defining a business problem in natural language and a "Predictive Notebook" that auto-generates the necessary SQL queries to build a custom model.

Pecan operates on a subscription-based model, generating revenue by providing access to its platform. It targets a wide array of industries, including fintech, retail, insurance, CPG, and mobile gaming, serving clients of all sizes. Use cases are diverse, focusing on revenue-impacting outcomes such as predicting customer churn, demand forecasting, identifying upselling opportunities, fraud prevention, and calculating customer lifetime value. By empowering business analysts to create and deploy their own predictive models, Pecan aims to bridge the data science scarcity gap and enable organizations to compete with tech giants. The company has secured substantial funding, including a $66 million Series C round in February 2022, bringing its total funding to over $100 million from investors like Insight Partners, GGV Capital, and Google Ventures.

Keywords: predictive analytics, business intelligence, low-code AI platform, automated machine learning, Predictive GenAI, demand forecasting, customer churn prediction, data science automation, SQL analytics, fraud detection, customer lifetime value, lead scoring, AI for business analysts, neural networks, predictive modeling, revenue optimization, CPG analytics, retail analytics, fintech AI, marketing mix modeling