Lunos has launched a free cash flow forecasting product designed to give finance teams a more dynamic alternative to spreadsheet-based forecasting, extending the company’s AI-driven finance automation strategy beyond accounts receivable and accounts payable workflows.
The standalone product connects directly with QuickBooks, NetSuite or Xero to synchronize accounting data and maintain a live forecast as underlying financial information changes. Users can also build a forecast by uploading accounts receivable, accounts payable and bank statement data.
What makes the launch particularly relevant to ERP and finance leaders is not simply the use of AI. Lunos is attempting to address a persistent weakness in financial planning: forecasts can quickly lose value when the assumptions behind them change faster than finance teams can update their models.
Rather than requiring users to rebuild formulas or manually adjust multiple assumptions, the new product allows finance teams to describe business changes in everyday language and incorporate them into the forecast.
Bringing Operational Changes Directly into the Cash Forecast
Cash forecasting often sits between historical accounting data and assumptions about what will happen next. While ERP and accounting systems provide the underlying transactions, finance teams frequently move that information into spreadsheets to model hiring, customer payments, renewals, churn and other events.
Lunos is seeking to shorten that gap.
A finance team could, for example, tell the system that a customer renewal has moved to December, that another customer will churn at the end of the third quarter, or that two engineers will join the company in October. Those changes can then be reflected in the forecast without manually restructuring the underlying model.
The product also allows users to ask questions of the forecast and compare previous forecasts against actual results, providing finance teams with a way to see not only the expected cash position but also how accurately earlier assumptions played out.
Duncan Barrigan, Founder and CEO of Lunos, said the goal is to make forecasting more closely reflect the current state of the business.
“We are proud to give finance teams a live cash flow forecast product that connects directly to their accounting data, reflects how customers actually pay and can be updated in simple, everyday language.”
Lunos is making the forecasting product available free of charge, positioning it as an accessible entry point for businesses that may otherwise rely heavily on spreadsheets for short- and medium-term cash planning.
Customer Payment Behavior Adds Another Layer to Forecasting
One of the more significant aspects of the product is its approach to accounts receivable.
A forecast based solely on invoice due dates can create a misleading picture of future liquidity if customers routinely pay earlier or later than their contractual terms. Lunos says its forecasting product uses individual customer payment histories to estimate when cash is actually likely to arrive.
The capability uses the same prediction engine as the company’s accounts receivable agent.
That distinction matters because cash flow forecasting is ultimately concerned with timing, not simply whether revenue has been invoiced. Two customers with identical payment terms may have very different real-world payment patterns, and incorporating that behavioral history could give finance teams a more realistic view of expected receipts.
For ERP environments, this also illustrates a broader direction in financial automation: transactional systems remain the system of record, while AI-driven applications increasingly attempt to interpret the behavior contained within that data and turn it into forward-looking information.
A Shared Forecast Rather Than Another Spreadsheet
Lunos is also addressing the collaborative side of forecasting.
The platform provides a single live forecast that can be shared across finance teams, executives and board members. As accounting information and assumptions change, users can work from the same view rather than circulating different spreadsheet versions.
Richard Atkins, Director of Accounting at Lunos customer Crisp, said the system has reduced the spreadsheet maintenance previously associated with the company’s forecasting process.
“The forecast is easy to update, reflects how our customers actually pay and gives our team confidence that we’re making decisions based on current information.”
The ability to compare forecasts with actual outcomes could also make the forecasting process more accountable. Instead of simply replacing one forecast with the next, finance teams can examine where expectations diverged from reality and potentially refine future assumptions.
AI Moves Closer to the Finance Planning Layer
The launch comes as AI is increasingly moving beyond discrete automation tasks in enterprise finance.
Accounts payable invoice processing, collections communications, reconciliation and transaction matching have already become prominent areas for AI-assisted automation. Forecasting pushes AI further into the decision-support layer, where the challenge is not only processing transactions but interpreting their likely effect on future business conditions.
Lunos’ approach is notable because it combines three elements that have traditionally been separated: accounting-system data, behavioral predictions based on customer payment history, and scenario modeling through natural-language interaction.
However, easier scenario creation does not eliminate the need for financial judgment. Forecast quality will still depend on the quality and completeness of underlying accounting data and on whether the assumptions supplied by users accurately reflect expected business events.
For finance leaders, that makes the emerging role of AI in forecasting less about replacing financial planning and more about reducing the manual effort required to keep planning models current.
Lunos’ cash flow forecasting product is generally available as of September 22. As finance applications become more conversational and increasingly connected to live ERP and accounting data, the larger question will be whether these tools can move forecasting away from periodic spreadsheet exercises toward a continuously updated view of enterprise liquidity.
ERP News Editorial Team
The ERPNews Editorial Team covers global developments in ERP (Enterprise Resource Planning), enterprise software, cloud platforms, AI, automation, and digital transformation, providing independent news and editorial analysis for senior business and technology leaders. Our reporting focuses on market signals, strategic shifts, and enterprise impact across the ERP and enterprise technology ecosystem.
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