AI-Driven Cash Flow Forecasting & Liquidity Planning on AWS

A ready-to-deploy, AWS-native accelerator, Rysun's Cash Flow Forecasting and Liquidity Planning solution enables enterprises to gain predictive visibility into cash inflows, outflows, liquidity positions, and aging balances. The module enables finance teams to move from reactive, spreadsheet-driven forecasting to proactive, scenario-based decision-making - improving working capital control and reducing liquidity risk.

Designed for finance and technology leaders, the solution reduces time-to-value by providing a proven forecasting framework that can be rapidly adapted to enterprise financial environments.

Why Cash Flow Forecasting Matters Enterprises face increasing cash flow uncertainty driven by volatile demand, complex payment cycles, and fragmented financial data. Traditional spreadsheet-based forecasting methods are slow, error-prone, and reactive - limiting the ability of finance teams to proactively manage liquidity and working capital risk.

Forecasting Intelligence The solution applies proven time-series forecasting techniques - including ARIMA, SARIMA, and Prophet - to capture trend, seasonality, and business-specific cycles. Models can be tuned to your data maturity, forecasting horizon, and enterprise complexity, enabling reliable short- and medium-term liquidity projections. The solution supports continuous refinement as new financial data becomes available.

Solution Highlights Pre-built forecasting capability that helps organizations move from reactive cash monitoring to predictive, scenario-driven liquidity planning. Key outcomes include:

• Predictive forecasts of cash inflows, outflows, and net cash position
• Aging balance forecasting for receivables and payables by cohort to identify timing risks
• Scenario-based liquidity planning to model and evaluate optimistic, conservative, and stress conditions
• ERP & general ledger integration for automated data ingestion and recurring forecast refreshes
• Faster time-to-value through a ready-to-deploy, AWS-native architecture

AWS-Native Architecture The solution is implemented using AWS-native services to ensure scalability, security, and operational reliability. Typical architectures leverage Amazon SageMaker for model training and deployment, AWS Lambda for orchestration, Amazon S3 for secure data storage, and Amazon CloudWatch (and optional AWS X-Ray) for monitoring and operational visibility. Secure access and authentication are implemented using Amazon Cognito / AWS IAM. Architecture patterns are aligned to AWS best practices and client's environment, data sources, and governance requirements.

Proven Impact In benchmark implementations, teams have achieved measurable improvements such as significant reduction in manual financial analysis effort (e.g., up to ~60%) and strong forecast accuracy targets (e.g., single-digit MAPE), depending on data quality and process maturity.

Start with a focused discovery workshop, rapid deployment of the accelerator, or extension of existing cash forecasting capabilities - accelerating time to value based on AI readiness and liquidity planning objectives.