Institutional-grade predictive analytics for your supplemental portfolio.
Skellig Capithorn uses adaptive AI to align market volatility with your specific risk profile, so decisions are made on your terms even when you are working.
Skellig Capithorn uses adaptive AI to align market volatility with your specific risk profile, so decisions are made on your terms even when you are working.
Independent contractors and platform-based workers manage irregular hours and unpredictable income. Between jobs, there is rarely time to track intraday price movements or reassess exposure.
Skellig Capithorn closes that gap with continuous, automated oversight. The system monitors conditions around the clock and applies calibration rules you have already set, so your capital is never left unattended between shifts.
The engine does not apply a fixed formula to every account. It adjusts to your capital, your history, and your stated tolerance, then updates as those inputs change.
The model observes how your account responds to volatility over time and revises its assumptions about your risk tolerance accordingly, rather than relying on a static questionnaire.
Market data is processed continuously. Positions and exposure levels are reviewed as conditions shift, not on a fixed daily schedule.
Protective stops scale with your capital. As your risk tolerance evolves, whether through growth or drawdown, the system moves those thresholds to reflect the change.
Link your account through an encrypted, read-and-execute connection. No manual data entry is required after setup.
Set the minimum threshold you are prepared to accept. This becomes the baseline the engine calibrates against.
The engine acts on predictive models within your defined parameters. You can review or adjust those parameters at any time.
Every recommendation is derived from high-velocity market data combined with patterns drawn from historical cycles. Nothing is generated from a black box: the same inputs are available for your own review inside the platform.
Source data feeding the models includes:
You set the operational parameters and can revise or suspend them at any time. The AI executes within those boundaries; it does not override them. Data is encrypted in transit and at rest, and connections use read-and-execute permissions only, never withdrawal access.