Almeley applies predictive modelling to monitor volatility and limit drawdowns, so decisions are supported by data rather than instinct.
Built for sophisticated investors conducting independent due diligence on digital asset risk.Crypto markets move outside standard trading hours and often without clear catalysts. Investors who monitor positions manually tend to make decisions late, after a loss has compounded, or early, out of fatigue rather than analysis.
The result is a pattern familiar to anyone who has held a volatile position through a drawdown: conviction weakens exactly when discipline matters most. Almeley was built to remove that dependency on continuous human attention, without removing human oversight.
Static stop-loss orders exit at a predetermined price regardless of context, which often triggers on short-term noise. Almeley's system instead analyses volatility patterns, liquidity conditions, and historical drawdown behaviour to adjust exit thresholds dynamically, aiming to distinguish temporary fluctuation from sustained directional risk.
Visualised internally as a moving drawdown corridor, tightening in high-volatility regimes and widening when conditions stabilise.
Transparency about process matters more to us than the appearance of certainty. The following three stages describe what the platform actually does.
The system continuously ingests price action, order book depth, and on-chain settlement data across major exchanges, normalising it into a consistent format for analysis.
Statistical models trained on historical volatility events estimate the probability of a sustained drawdown versus short-term noise, producing a risk score rather than a price prediction.
When the risk score crosses a defined threshold, the platform recommends or, where authorised, executes a graduated exit designed to reduce exposure without exiting the market entirely.
No predictive model can eliminate loss. Almeley is designed to reduce the severity and frequency of drawdowns under defined conditions; it does not guarantee returns or remove market risk.
Portfolio-level views aggregate drawdown risk across multiple holdings rather than treating each position in isolation. Reporting is formatted for review alongside existing risk frameworks, with exportable data for audit and compliance purposes.
Drawdown thresholds are set once, in plain terms, and applied consistently thereafter. The platform does not require constant supervision, and every automated action is recorded with the reasoning behind it.
Rather than executing automatically, alerts can be configured to notify the investor when risk conditions change materially, leaving the final decision with the account holder at all times.
The system assigns a continuously updated risk score to each position based on volatility, liquidity, and historical drawdown patterns. Action is only taken when that score crosses a threshold set during account configuration, and the triggering data is retained for review.
Almeley connects to exchange accounts through permissioned, read-and-trade API keys that never expose withdrawal rights. Data in transit and at rest is encrypted, and access logs are available to account holders on request.
Integration currently supports major centralised exchanges via API connection. Coverage is reviewed periodically, and supported venues are confirmed during onboarding rather than listed generically, since availability can change.
Fee structures depend on account size and mandate type, and are confirmed directly with each applicant before any commitment is made. We do not publish indicative figures that could mislead prospective clients with different requirements.
Request access to see how the risk model is structured, what data it relies on, and where its limitations sit. There is no obligation to proceed afterwards.
Request AccessNo trial charges. No automatic enrolment. Access is reviewed manually before activation.