We already do rolling cash flow forecasts in Excel. What does Armqu add?

Excel models are only as accurate as the inputs you feed them, and those inputs require manual assembly from systems that do not talk to each other. Armqu replaces that assembly process with a live connected model. The question it answers is not what do we forecast, but what will this specific decision do to your cash position in the next 90 days.

We have an ERP. Shouldn't it handle cash flow forecasting?

ERP systems record what has happened. They do not model what a decision will cost before you commit, because they cannot see across procurement, HR, inventory, and debt service simultaneously. Armqu connects to your ERP as one data source and adds the cross-system simulation layer your ERP was not designed to provide.

How accurate is Armqu's cash flow agent? What if my data has gaps?

Armqu does not use AI to generate figures. The platform calculates answers using your data, organised into a model built specifically for your operation during implementation, based on definitions and formulas agreed with your team. The AI explains those results and surfaces anomalies. It does not invent numbers. Every answer shows what data was used, where it came from, and when it was last updated. If data is incomplete or missing, the platform flags it rather than providing an uncertain answer.

Where does our financial data go? Who can see it?

Your data is organised into a proprietary, client-specific model that is completely separate from every other Armqu customer. The AI does not receive your raw financial records. It receives only a short structured summary of pre-calculated results, along with the sources used. Your data is never used to train any shared model. General product improvements are based on aggregated usage trends, not on your data. Your team defines which users access which data at setup, and those boundaries do not change without your authorisation.

How long does it take to get a live cash position running with Armqu?

Armqu's cash flow agent goes live in 6 to 9 weeks. Armqu's implementation team maps your operation, connects your data sources, and calibrates the simulation to your specific customers, vendor terms, and payment patterns. Your team does not build it.

What happens when the agent flags something? Who approves it?

Armqu operates on a human-in-the-loop model. The agent surfaces risks and recommendations with the full context behind them. Routine execution runs autonomously. Decisions that cross your approval threshold come to you with everything you need to act in one place. The agent does not go beyond the authority boundaries you set at setup.

Cash Flow & Liquidity Simulation AI Agent

Your 90-day cash position is not a report. It is a decision you are making right now.

Armqu's cash flow agent connects every system that moves cash in your operation, models what each commitment will cost before you make it, and flags the gaps before they appear on your bank statement.

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The problem

Your ERP tells you what happened last quarter. Your finance model tells you what might happen next month, based on last quarter's costs. Neither tells you what this decision will do to your cash position in 47 days.

Every input to a credible cash model lives in a different system. Customer payment behaviour is in the ERP. Open purchase orders are in procurement. Payroll is in HR. Loan schedules are in a spreadsheet. Vendor penalty clauses are in contracts nobody has digitized. Inventory tied up in slow-moving stock does not appear as a liquidity drain until it is too late.

You delay a supplier payment by 15 days to preserve cash. A penalty clause triggers. The saving disappears. The relationship does not recover.

You sign a retail order without modelling the working capital requirement. A 6-week cash trough appears that your bank covenant cannot absorb.

Your AR team chases payment on contracted terms. That customer's actual payment behaviour runs 18 days longer. Nobody updated the forecast.

Connected to everything that matters

A credible 90-day cash position requires at least 12 data inputs across 5 systems. Armqu's cash flow agent connects all of them, models them against your actual customer payment behaviour and vendor terms, and gives you a live position.

Inflows

Invoices issued, actual payment behaviour per customer, open orders not yet invoiced, deposits, credit notes, supplier financing drawn.

Operational outflows

Payroll by site, tax and VAT schedules, variable utility costs, lease and insurance obligations.

CapEx & debt

Loan repayment by date, leasing instalments, CapEx payment milestones, maintenance contracts

Supplier outflows

Vendor invoices by due date, payment terms, penalty clauses, open POs not yet invoiced, raw material price revisions.

Working capital

Inventory by raw material, WIP and finished goods; DSO and DPO per customer and vendor; safety stock requirements.

See how this works for F&B manufacturers

Armqu Platform

From 3 days, to 5 minutes

Cash position assembled manually, 2 to 3 days, and asking 3 people.

Contracted payment terms used in the model; actual customer behaviour not tracked

Penalty clauses checked manually, when someone remembers

Slow-moving stock invisible as a liquidity drain

Cash gap discovered 4 to 6 weeks after the decision

Live position updated continuously across all connected sources

Actual payment behaviour modelled per customer

Penalty exposure flagged before the payment decision is made

Inventory cash exposure surfaced continuously

Full consequence visible before you commit

FAQs:

Excel models are only as accurate as the inputs you feed them, and those inputs require manual assembly from systems that do not talk to each other. Armqu replaces that assembly process with a live connected model. The question it answers is not "what do we forecast?" It is "what will this specific decision do to your cash position in the next 90 days?"
ERP systems record what has happened. They do not model what a decision will cost before you commit, because they cannot see across procurement, HR, inventory, and debt service simultaneously. Armqu connects to your ERP as one data source and adds the cross-system simulation layer your ERP was not designed to provide.
Armqu does not use the AI to generate figures. The platform calculates answers using your data, organised into a model built specifically for your operation during implementation, based on definitions and formulas agreed with your team. The AI explains those results and surfaces anomalies. It does not invent numbers. Every answer shows what data was used, where it came from, and when it was last updated. If data is incomplete or missing, the platform flags it rather than providing an uncertain answer.
Your data is organised into a proprietary, client-specific model that is completely separate from every other Armqu customer. The AI does not receive your raw financial records. It receives only a short structured summary of pre-calculated results, along with the sources used. Your data is never used to train any shared model. General product improvements are based on aggregated usage trends, not on your data. Your team defines which users access which data at setup, and those boundaries do not change without your authorisation.
Armqu operates on a human-in-the-loop model. The agent surfaces risks and recommendations with the full context behind them. Routine execution runs autonomously. Decisions that cross your approval threshold come to you with everything you need to act in one place. The agent does not go beyond the authority boundaries you set at setup.

Book a demo

Bring real decisions your team made in the last 30 days: a payment timing call, an order acceptance under margin pressure, a procurement commitment with penalty exposure. We will model them against your operational context and show you what a live position would have surfaced before you committed.