Connect advances, orders, receipts, invoices and payments into one traceable procure-to-pay view.
Synthetic data · illustrative analysis · select a thumbnail, swipe, or hover the thumbnail rail and use the mouse wheel
Finance teams are expected to protect cash, support capital and investment decisions, and show management what comes next. Too often, downloading, cleaning, linking, reconciling and explaining the data consumes the time needed for that work.
Illustrative starting actions
Your team moves from assembling the evidence
to acting on the exceptions that matter.Technology carries the recurring work. Finance retains judgment and control.
Bring together operational, ledger, bank, aggregator-settlement and GST/tax data.
Establish a trusted financial foundation.
Trace movements to transactions and drivers.
Translate current behaviour into forward impact.
Rank interventions, assign owners and track outcomes.
Evidence attached. Financial impact visible. Judgment remains with finance.
SIX WORKED DEMONSTRATIONS
Each demonstration runs on the same synthetic finance dataset, from the CFO's question through reconciliation to owned work and value.
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It means connecting and reconciling finance and operating data so management can understand the evidence, financial impact and action behind a business question. It does not mean investment research, lending intelligence, personal finance or financial-crime intelligence.
No. A dashboard is one possible presentation layer. Financial intelligence includes the work required to connect, reconcile, interpret and translate underlying data into a management decision.
They overlap, but they are not identical. Business intelligence can support analysis across many functions. Corporate financial intelligence applies finance-specific reconciliation, controls, definitions and judgment to questions affecting cash, performance and planning.
No. It can use ordinary data integration, reconciliation rules, workflow automation and analytical methods. AI may assist selected tasks, but it should not replace evidence, controls or accountable human review.
No. Its purpose is to improve the evidence available to finance and management. Interpretation, commercial judgment, approval and accountability remain human responsibilities.
That depends on the question. Relevant sources might include ledgers, banks, invoices, receipts, operational data, budgets and forecasts. The starting point should be the business decision—not a request to combine every available dataset.
No universal revenue threshold defines when it becomes useful. Madhilaiya focuses on companies above ₹5 crore, where increasing transaction, reporting and decision complexity may make structured support more relevant.
Madhilaiya is designed for companies with revenue above ₹5 crore. The relevant starting point is a finance problem that needs clearer data, reconciliation, explanation or management action.
No. Every demonstration on this page uses synthetic finance data. The figures and findings illustrate the analysis and workflow; they are not client results or testimonials.
Book a 30-minute demonstration, call or email Madhilaiya. Bring one finance problem and the systems or reports involved so the discussion can stay focused.
We diagnose, build and hand over.
Your team owns the decisions that follow.
Start with a demo. Walk through a relevant problem and inspect how the findings are supported.
A shared understandingAgree the scope and required data. Receive findings and the potential recovery, savings or financial improvement.
A scoped diagnosticEstablish the linkages, reconciliation, exception reporting and any agreed reminders or briefings.
A tailored working layerYour team acts on the insights. Agree handholding and support for system changes that affect the linkages.
A client-operated workflow*Diagnostic response within one week of receiving the agreed data. Build scope and ongoing support are agreed separately.
FROM QUESTION TO MEASURABLE VALUE
For companies above ₹5 crore. Start with one finance problem and the data needed to examine it.