Zone & Co Unveils Its Agentic Direction for Treasury with AI-Powered Cash Forecasting and Scenario Planning

Expanding capabilities will help finance teams manage working capital, cash liquidity, and financial planning with greater confidence

Zone & Co, a leading ERP-native, AI-powered financial operations platform, unveiled its direction for the future of treasury workflows, introducing ZoneLiquidity with AI-powered cash forecasting and a Scenario Planning Agent designed to help finance teams better manage working capital, liquidity, and financial decision-making.

For many finance teams, cash forecasting remains a manual, spreadsheet-driven process. Teams routinely pull data from accounts receivable, accounts payable, and multiple bank accounts to build rolling forecasts that are difficult to maintain and often outdated before decisions can be made. Testing scenarios such as delayed customer payments, supplier renegotiations, or changing spending patterns frequently requires rebuilding models by hand, slowing decision-making when business conditions change. Traditional standalone treasury and forecasting tools often add another layer of complexity, pulling financial data away from the system of record into separate models that must be maintained, leaving finance teams planning against a stale snapshot rather than current reality.

To address these challenges, Zone is expanding the capabilities available within ZoneReconcile and its broader treasury workflow, introducing AI-powered cash forecasting and a Scenario Planning Agent that help finance teams understand current liquidity, evaluate future cash positions, and investigate the factors driving change.

Read More on Fintech : Global Fintech Interview with Rob Young, Managing Director – UK at InDebted

ZoneLiquidity combines reconciled financial data, bank activity, accounts receivable, and accounts payable information to provide a forward-looking view of cash, working capital and opportunities to optimize the cash conversion cycle. At its core is a forecast engine built on a proven foundation-model approach to time-series forecasting which produces forecasts grounded in a company’s own cash history without a lengthy, hand-built modeling project. Finance teams can gain visibility into global consolidated cash positions, analyze forecast variance, and better understand how operational activity may influence future cash outcomes.

Complementing these capabilities is the Scenario Planning Agent, Zone’s treasury-focused Subject Matter Agent, that allows finance teams to test assumptions. Rather than rebuilding static models for every “what-if” question, teams can dynamically simulate shifts in collections, procurement, and payment timing to see the immediate impact on liquidity. The result is greater agility to evaluate scenarios, course-correct when conditions change, and make more informed financial decisions.

“Finance teams don’t need more spreadsheets. They need better answers,” said Thomas Kim, CEO of Zone & Co. “Cash decisions are some of the most important calls finance teams make, yet many organizations still rely on manual processes to get there. We’re building forecasting where the data is already reconciled and true – with best-in-class forecasting science and agents that reason over a company’s real numbers – so finance can move from reacting to anticipating, with confidence.”

These new capabilities build on the foundation of ZoneReconcile and Bank Connectivity, which already help more than 1,000 customers automate transaction matching and maintain a trusted view of cash activity across accounts and entities. Together, they mark the beginning of Zone’s broader treasury vision: a connected workflow that helps finance teams understand where cash is, where it is going, and what actions they should take next. Over time, Zone plans to expand this foundation with additional treasury capabilities designed to bring visibility, planning, and decision-making into a single experience.

The post Zone & Co Unveils Its Agentic Direction for Treasury with AI-Powered Cash Forecasting and Scenario Planning appeared first on GlobalFinTechSeries.