AI Decision-Optimization Platform
Vandelixio applies predictive models to market data and publishes the resulting performance record openly. Investors review the log before any commitment.
Vandelixio records each model recommendation at the moment it is generated, not after results are visible. This ordering prevents retroactive selection of favorable outcomes.
The resulting log is exposed for external review. Investors and analysts can trace individual decisions back to the input data that produced them.
Vandelixio does not claim to forecast prices. It ranks available actions by risk-adjusted expected outcome, given current data.
Order books, on-chain flows, and macro indicators are processed continuously and normalized into a single decision frame.
Each candidate action is scored against multiple market scenarios before execution, reducing exposure to single-outcome bets.
Position sizing and timing rules limit how much capital any single recommendation can move at once.
The engine treats every trade as a constrained optimization problem: maximize expected risk-adjusted return while respecting exposure limits set for the account.
Model outputs are recalculated on a fixed interval rather than continuously, which keeps decisions auditable and reduces reaction to short-lived noise.
Drawdown thresholds are enforced automatically. If a portfolio breaches its configured limit, new positions are paused until the limit resets.
These are the operational advantages firms typically cite when evaluating Vandelixio against manual analysis workflows.
Data refresh cycles run in minutes, not days, so recommendations reflect current market structure rather than end-of-week reviews.
The same engine supports a single desk or multiple portfolios in parallel, with outputs scaled to each account's risk configuration.
Orders are sized and sequenced to limit slippage, with execution logs retained for post-trade review and compliance reporting.
Vandelixio was built on a simple constraint: no recommendation is edited or removed once it is published to the log, regardless of outcome.
This discipline is what allows external reviewers to evaluate the model on its actual track record, rather than a curated summary of it.
Onboarding is designed to require minimal operational change on the client side.
Connect existing exchange or custody accounts via read/execute API keys. No transfer of custody to Vandelixio occurs at this stage.
The engine runs a baseline assessment of current holdings against your stated risk parameters before any action is proposed.
Approved recommendations are executed within the constraints set during onboarding, and each action is added to the public log.
Data is processed on infrastructure located within the EU, subject to GDPR requirements. Vandelixio does not sell or share account-level data with third parties.
Hard limits on position size and drawdown are set per account and enforced at the execution layer, independent of the recommendation engine itself.
Yes. Clients retain custody of their assets at all times; Vandelixio operates under permissions that can be revoked immediately from the account dashboard.
Entries are timestamped at generation and cannot be edited retroactively. External reviewers sample and cross-check entries against raw market data monthly.
Request access to the full performance record and a walkthrough of current risk parameters before committing any capital.