Aipom AI applies predictive modelling and real-time market analysis to your business's cash reserves, producing allocation suggestions calibrated to your risk tolerance. Konto miinimumi pole, fikseeritud sisenemisläve pole.
Alustage optimeerimist koheMost small businesses hold working capital in low-yield current accounts for the sake of liquidity. See ettevaatus on mõistlik, kuid see pole tasuta. Every pound sitting idle is a pound not contributing to strategic cash flow, and the gap between what it earns and what it could earn compounds over time.
Aipom AI was built around a narrower question: how much of a business's reserve can be put to productive use without compromising the liquidity it needs day to day. The answer depends on data — inflows, outflows, seasonality, and market conditions — analysed continuously rather than reviewed once a quarter.
The platform is built to handle the data analysis a treasury team would normally perform manually, then present the conclusions in plain terms.
The system forecasts how different allocations might behave under varying market conditions, giving you a measurable view of downside exposure before any capital moves.
Market data is ingested and reassessed continuously rather than on a fixed schedule, so recommendations reflect current conditions instead of last month's figures.
Based on your stated liquidity needs and risk tolerance, the engine proposes specific allocation ranges, each with a clear rationale attached.
Each suggestion the platform produces can be traced back through three stages, so you are not asked to act on a conclusion without understanding how it was reached.
Account balances, inflow and outflow patterns, and relevant market indicators are collected and normalised into a consistent dataset for analysis.
Predictive models assess the dataset against historical patterns and current conditions, identifying ranges of likely outcomes and associated risk levels.
The analysis is converted into a short list of allocation options, each stated with its expected risk profile and liquidity impact.
A retailer with a strong Q4 builds a temporary cash buffer. Rather than letting it sit flat for three months, the surplus is allocated to short-duration, low-volatility options that can be released quickly when needed.
A consultancy sets aside a portion of monthly profit for future expansion. The engine recommends a gradually adjusted allocation as the reserve grows and the time horizon shortens.
A supplier dependent on one large contract uses the platform's risk modelling to understand how exposed its reserves are, and adjusts allocation to reduce correlated risk.
Aipom AI was developed on the premise that the tools used by larger institutions to manage cash reserves — predictive modelling, continuous market monitoring, structured risk assessment — are not inherently expensive to run. What has historically limited access is account minimums and manual advisory overhead.
Analüüsi automatiseerimise ja deposiidiläve eemaldamisega muutub sama kategooria otsustustoetus kättesaadavaks mõne tuhande naela reservi haldavale ettevõttele, mitte ainult neile, kes haldavad miljoneid.
Kõik Aipom AI-i jaotamise soovitused põhinevad nende loomise hetkel kehtivatel andmetel. Alustuseks ei ole minimaalset sissemakset ega kohustust enne selle ülevaatamist ühegi soovituse järgi tegutseda.