Features built around risk, not noise
Xorvelima combines predictive risk modelling with automated stop-loss logic, giving AI-managed crypto portfolios a consistent, rules-based layer of protection.
Designed for portfolios that need defined risk boundaries, not reactive guesswork.
Risk monitoring and portfolio views, side by side.
A structured approach to volatility
Crypto portfolios managed by automated strategies face constant exposure to sudden drawdowns. Xorvelima is built to address that exposure directly, with modelling and thresholds that operate continuously rather than on an ad-hoc basis.
- Manual risk checks lag behind fast-moving markets
- Static stop-loss levels don't adapt to changing volatility
- Fragmented tools make it hard to see exposure in one place
- Without defined thresholds, losses can compound before action is taken
Core feature set
Each feature addresses a specific part of the risk-management workflow for AI-managed crypto portfolios.
Predictive Risk Modelling
Continuously evaluates portfolio data against historical volatility patterns to flag conditions associated with elevated drawdown risk, before losses accumulate.
Automated Stop-Loss Protection
Applies configurable stop-loss rules across positions, executing according to pre-set parameters rather than relying on manual intervention during volatile periods.
Portfolio Exposure Dashboard
Consolidates holdings, risk scores, and threshold status into a single view, reducing the need to cross-reference multiple tools during fast-moving markets.
Threshold Customisation
Risk tolerance varies by strategy and asset. Thresholds can be adjusted per portfolio segment rather than applied uniformly across every position.
Historical Scenario Review
Past model behaviour and threshold triggers are logged and reviewable, supporting ongoing evaluation of how risk parameters performed under prior conditions.
Alert & Status Reporting
Status changes and threshold triggers are surfaced clearly within the dashboard, keeping attention focused on positions that require review.
Predictive modelling identifies patterns in historical and current data; it does not guarantee future market behaviour. All features operate within the risk parameters configured for each portfolio and are not a substitute for independent judgement.
How the features work together
A continuous cycle from data intake to protective action.
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01
Data intake
Portfolio positions and market data are ingested on an ongoing basis.
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02
Risk scoring
Positions are evaluated against the predictive risk model to produce current exposure scores.
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03
Threshold check
Scores are compared against the configured thresholds for each portfolio segment.
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04
Automated action
When a threshold is reached, stop-loss logic executes according to pre-set rules.
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05
Review & adjust
Outcomes are logged in the dashboard, supporting threshold review and future adjustments.
Questions about configuration options? See the FAQ for details.
With and without Xorvelima
A general comparison of manual versus structured risk management.
| Area | Manual approach | With Xorvelima |
|---|---|---|
| Risk detection | Periodic, manual review of positions | Continuous predictive scoring |
| Stop-loss execution | Manually triggered, subject to delay | Automated, rules-based execution |
| Visibility | Spread across separate tools | Consolidated in one dashboard |
| Threshold consistency | Varies by individual judgement | Defined and applied consistently |
| Historical review | Ad-hoc, difficult to reconstruct | Logged and available for review |
This comparison describes general workflow differences and is not a guarantee of specific outcomes. Cryptoasset investments carry a high degree of risk, and automated features do not eliminate the possibility of loss.
See the features in context
Explore how predictive modelling, thresholds, and automated protection fit together inside the Xorvelima dashboard.
Xorvelima provides risk-management tooling for informational purposes. It does not constitute financial advice, and past model behaviour is not indicative of future results.