Terelise Pomirel analyzes your payment flows in real time and continuously adapts investment recommendations to your individual risk tolerance - comprehensibly and without manual spreadsheets.
Start your free analysisMany companies hold cash reserves that exceed what is operationally necessary. The reason is rarely poor planning, but rather the speed with which market conditions change: traditional analyzes - quarterly reports, manual Excel models - depict risks that are already out of date at the time of evaluation.
The result is a structural dilemma: if you plan too cautiously, you miss out on returns. Anyone who acts too aggressively without knowing their own risk tolerance will endanger liquidity at the crucial moment.
The platform combines historical patterns with current market data and derives recommendations for action that adapt to your liquidity situation.
Models recognize recurring patterns in payment flows and market movements and, on this basis, estimate what proportion of liquidity can operate without operational risk.
Every recommendation is checked against your stored risk profile. If a market situation deviates from the learned limits, the system automatically reduces the suggested exposure.
Changes in the interest rate structure, exchange rates or incoming payments are continually incorporated into the analysis, so that recommendations are not based on outdated snapshots.
The algorithm does not start with assumptions, but with a structured learning phase in which your specifications and your actual behavior are compared.
Accounts, accounting systems and relevant market data are securely connected. The system uses this to create a consolidated picture of your liquidity structure.
In the adaptive learning phase, the AI compares your information about risk aversion with historical decisions and uses this to calibrate an individual tolerance profile.
Based on the calibrated profile, the system continually suggests adjustments and learns from every feedback without changing the profile on its own.
A wholesale company records significantly higher incoming payments in the fourth quarter than in the rest of the year. Instead of holding the reserve without interest until the next investment,
An owner-managed service company is planning to expand in two to three years. Until then, the capital should not lose any real value. The system proposes a structure that balances the preservation of purchasing power with the company's predetermined risk tolerance and adjusts it as soon as interest rates or inflation expectations shift.
Recommendations are based on documented model assumptions, not on experience reports. You can trace every decision back to the underlying database.
Data storage and processing takes place on servers within the EU, in accordance with the requirements of the GDPR and with clearly defined access rights.
Your financial data will only be used to calculate your own recommendations and will not be merged with other mandates.
Each recommendation is stored and visible with the relevant key figures – confidence interval, assumed risk limit, time horizon.
Terelise Pomirel was developed to close the gap between available financial data and actually used decision-making bases. Instead of blanket investment suggestions, the platform provides recommendations derived from your company's specific payment patterns and documented risk tolerance.
The focus is on comprehensible, logically justified optimization - not on forecasts that cannot be checked afterwards.
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