Libre Datavre continuously analyzes your excess cash flow, models different investment scenarios and offers you arbitrages adapted to your real risk tolerance, not to a market average.
Overview of the dashboard: evolution of available cash, distribution between immediate liquidity and optimized capital, and volatility indicator updated every business day.
Indicative illustration of the gap between uninvested cash and an allocation adjusted to the risk profile. Past or simulated performance is no guarantee of future results.
Excess cash left in a current account or standard savings account does not generate sufficient return to compensate for inflation. For an SME, this represents a silent shortfall, rarely visible in traditional monthly dashboards.
The opposite reflex — investing this cash without method — exposes you to a poorly calibrated risk: too cautious, it changes nothing; too aggressive, it endangers the liquidity that the company needs on a daily basis.
Libre Datavre uses predictive models to evaluate, based on your actual flows and your deadlines, the share of cash that can be mobilized without weakening your operation. The system then adjusts its recommendations based on your risk tolerance, not a generic profile.
The integration is designed for a manager or financial director without a data team: each step remains visible and modifiable.
You link your professional bank accounts and, if necessary, your accounting software. Libre Datavre aggregates your incoming and outgoing flows to establish a clear view of your available cash flow, day by day.
A structured questionnaire and the history of your flows allow the model to estimate your real risk tolerance — not a standard category, but a profile specific to your activity and your deadlines.
The system offers allocation arbitrages that you validate or adjust. It continually relearns from your decisions to refine its recommendations, without ever acting for you without your agreement.
Each functionality answers a concrete question that SME managers ask themselves before entrusting part of their cash flow to an automated system.
The model cross-references your receipts, disbursements and seasonality to estimate, with a displayed confidence interval, the amount of cash actually available over 30, 60 or 90 days.
Rather than a fixed risk grid, the engine adjusts its parameters as you validate or reject recommendations, to converge towards an allocation that you are prepared to assume over time.
The dashboard is updated with each significant banking movement, with a history of decisions taken and their measured impact on the return and volatility of the capital invested.
Bank connections go through DSP2 certified aggregators. Data is encrypted at rest and in transit, and you retain the ability to revoke access at any time.
We prefer to explain how the system decides rather than brandishing results that we cannot guarantee.
The Adaptive Risk method is based on a simple principle: the model does not seek to maximize a theoretical return, it seeks to remain within the risk limits that you have validated, even when the markets evolve. Concretely, this means that the algorithm automatically reduces exposure to volatility as soon as it exceeds the threshold you have defined, and notifies you before any significant allocation change.
This approach is part of a logic of control, not total automation: you keep control of the final decisions, the system simply prepares and justifies each recommendation.
Each recommendation is accompanied by the factors that explain it: level of available liquidity, estimated investment horizon, and variation in risk compared to your current allocation.
Your banking and accounting data are never resold or used to train models intended for other clients without strict anonymization. You can request their deletion at any time.
Libre Datavre was born from an observation shared by many financial directors of SMEs: existing cash flow optimization tools are either too simplistic or reserved for large structures with dedicated teams. Our platform combines predictive models with an interface designed to remain understandable without training in quantitative finance.
The product team works primarily on two areas: the clarity of the explanations provided by the AI, and the possibility of regaining control at any time over each allocation decision.
Yes. The system always maintains an immediate liquidity reserve calculated from your declared maturities. The optimized portion is allocated to media chosen for their liquidity, and withdrawal requests are processed according to the deadlines specific to each media, clearly indicated before any allocation.
Each recommendation displays the criteria used: estimated risk level, investment horizon, and deviation from your current allocation. You can view the full history of decisions and adjustments made over time.
There is no arbitrary threshold imposed by the platform. In practice, the benefit of optimization becomes more significant from the moment your excess cash already covers your operating needs over several months; the initial diagnosis helps you assess it for your situation.
Connect your accounts, let the model estimate your risk profile, and then decide if you want to enable automated optimization.