Due diligence & investments.

Testing assumptions before committing capital

AI confronts assumptions with real data: revenue quality, critical dependencies and execution sustainability.

situations addressed

  • Growth assumptions insufficiently tested;
  • Revenue quality or customer recurrence insufficiently evidenced;
  • Critical customer, supplier or product dependencies underestimated;
  • Operational, financial or commercial risks identified too late in the investment process.

illustrative use cases

01: Revenue quality and commercial potential


Sales histories can reveal the real robustness of revenue: recurrence, concentration, dependency on certain categories, cross-selling potential or fragility of the customer basket.


In a distribution case, the analysis of customer purchases identified 4,660 profitable opportunities across 1,023 customers. This type of analysis helps distinguish genuinely actionable growth potential from an overly broad commercial assumption.

02: Customer attrition and revenue loss risk


Potential churn can weaken a business plan when customer loss is progressive, poorly monitored or artificially offset by acquisition.


In a banking case, the model targeted 333 customers out of 2,000, of whom 229 were actual churn cases. This type of approach helps test the resilience of existing revenue and the real cost of protecting the customer portfolio.

03: Financial strength and critical dependencies


Predictive analysis can help qualify the financial fragility of a target, a key customer, a critical supplier or a portfolio of companies.


The objective is not to replace financial due diligence, but to add a data-driven reading of weak signals: deterioration probability, economic exposure, dependencies and investigation priorities.

When should a diagnosis be initiated?

A diagnosis is relevant when three conditions are met:


  • financial, commercial or operational data is sufficiently available;
  • key assumptions in the case still require validation;
  • the investment, acquisition or capital allocation decision is exposed to material economic risk.



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