Pecan has announced the launch of what it calls the world’s first Predictive AI Agent, a new technology aimed at shifting organizations away from reactive decision-making and toward forward-looking action. The New York–based company says the agent enables business teams to turn raw operational data into reliable, production-ready predictions within minutes—without requiring support from data science teams.
The Predictive AI Agent lets users ask questions in natural language. For example, users can inquire about customers likely to churn, demand fluctuations, or sales opportunities that may close. The system handles the entire predictive process on its own. It translates business intent into predictive goals, prepares and validates data, builds models, and generates reliable predictions for teams to use right away.
A key differentiator, according to Pecan, is the agent’s ability to work with each organization’s unique data structure. Instead of working with assumed standardized data sets, the AI learns to work with raw, business-specific data and turns it into AI-ready inputs, which is where previous automation solutions have fallen short. The end product is not a static report or dashboard but a form of actionable foresight that is injected directly into existing tools like CRMs and data warehouses.
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Zohar Bronfman, CEO of Pecan, said the company is addressing a long-standing gap in enterprise analytics. “For years, businesses have invested billions in data platforms, dashboards, and analytics, yet the most critical decisions are still made too late. Customers churn only after disengaging. Demand is recognized only after inventory runs out. Revenue gaps surface when the quarter is already over. Not because companies lack data, but because their systems are fundamentally backward-looking. Modern organizations are built to explain what already happened, not to anticipate what will happen next, even as business cycles accelerate and the cost of late decisions continues to rise.”
Pecan positions its technology like generative AI did for content creation. However, it focuses on prediction instead of text. The agent is designed for predictive analytics. It includes statistical safeguards to lower risks like overfitting and data leakage. These are common issues with traditional AutoML tools.
Early adopters are already seeing impact. Bubble, a long-time Pecan customer, tested the agent in private trials late last year. “What changed for us was how quickly prediction became usable,” said Shai Eisenman, CEO at Bubble. “We didn’t need to restructure our data or rely on data science resources to get started. Teams could ask real business questions and get reliable predictions they could act on immediately. That shift from explaining what already happened to acting on what’s likely to happen changed how decisions get made across the business.”
Pecan is currently deployed across industries including e-commerce, fintech, gaming, and supply chain, with customers such as Nanit, Mars Wrigley, Kenvue, and SciPlay. The Predictive AI Agent is now generally available, reflecting Pecan’s broader ambition to make reliable foresight accessible to organizations of any size or technical maturity.
