Tuesday, February 10, 2026

Pecan Launches Predictive AI Agent for Real-Time Foresight

Pecan Launches Predictive AI Agent for Real-Time Foresight

Pecan has announced the launch of its Predictive AI Agent, a new solution designed to help organizations anticipate what will happen next and act before it’s too late. The agent enables business teams to move beyond hindsight by turning raw data into statistically validated predictions in minutes, without the need for data science expertise.

For the first time, teams can connect their existing data and ask questions in plain language, such as which customers are likely to churn, how demand may shift, or which deals are most likely to close. The agent then delivers production-grade predictions that are immediately actionable, allowing organizations to change course while outcomes are still uncertain.

What sets Pecan’s Predictive AI Agent apart is its ability to autonomously execute the entire predictive workflow. From translating business intent into predictive objectives to preparing data, validating models, and running predictions, the agent handles every step end to end. A long-standing challenge in predictive AI has been adapting to each company’s unique data structure, but Pecan addresses this by transforming raw, business-specific data into AI-ready datasets without assuming standardization. The result is not another dashboard or report, but foresight that teams can act on immediately.

According to Zohar Bronfman, CEO of Pecan, most organizations are still fundamentally backward-looking despite massive investments in data platforms and analytics. He explained that critical decisions are often made too late—not due to a lack of data, but because existing systems are designed to explain what already happened rather than anticipate what will happen next. As business cycles accelerate, the cost of delayed decisions continues to rise.

Bronfman likened Pecan’s breakthrough to the impact OpenAI had on generative AI. While generative AI tools made advanced capabilities accessible to everyday users, predictive AI has remained locked behind complex workflows and specialized teams. Pecan’s Predictive AI Agent aims to change that by making reliable, operational predictions accessible to business users at any level.

As planning windows shrink, reliance on hindsight has become an operational liability. Yet predictive modeling—the only way to operate ahead of outcomes—has traditionally required long development cycles and heavy involvement from data science teams. Pecan’s approach removes these barriers, allowing organizations to shift from reactive analysis to proactive decision-making across revenue, retention, and operations.

Early results from customers reinforce this shift. Bubble tested the agent privately in the fourth quarter, and CEO Shai Eisenman said the speed at which prediction became usable marked a turning point. Teams were able to ask real business questions and receive reliable predictions without restructuring data or relying on specialized resources, fundamentally changing how decisions were made across the organization.

Unlike generative AI systems optimized for text or traditional AutoML platforms that depend on manual workflows, Pecan’s agent is purpose-built for prediction on real business data. It combines natural-language accessibility with statistical safeguards designed to reduce common risks such as data leakage, overfitting, and unreliable models. Predictions are delivered directly into the tools teams already use, including data warehouses, CRMs, and operational systems.

Pecan is currently deployed across e-commerce, subscription, gaming, fintech, fulfillment, and supply chain organizations, with customers including Nanit, Little Spoon, SciPlay, ShipNetwork, Mars Wrigley, Kenvue, and others. The company’s long-term vision is to make reliable predictive capabilities accessible to every business, regardless of size or technical maturity.

Pecan’s Predictive AI Agent is now available to both new and existing customers, marking a significant step toward making foresight—not hindsight—a standard part of modern business decision-making.

 

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