Every feature built around one job: outcome-driven investing
AuraxAI combines automated data analysis, rules-based allocation, and historical backtesting into a single workflow — so you get a portfolio strategy that's tested before it's trusted, not after.
Core platform capabilities
The foundation of AuraxAI is a set of automated processes that replace manual research, spreadsheet tracking, and guesswork with a consistent, repeatable method.
Automated Data Ingestion
Market data, pricing histories, and asset-level metrics are pulled and structured continuously, removing the need to manually source or reconcile figures before making a decision.
AI Allocation Engine
Allocation weights are generated from defined rules and data inputs rather than discretionary calls, giving every portfolio a documented, auditable rationale.
Historical Backtesting
Every allocation approach is run against historical market periods before it's applied, so you can see how a strategy would have behaved in past conditions.
Risk-Managed Rebalancing
Portfolios are checked against risk thresholds on a set schedule, with rebalancing triggered automatically when allocations drift outside defined bands.
Transparent Reporting
Allocation changes, rebalancing events, and performance figures are logged and presented in a single dashboard, so nothing happens without a visible record.
Scheduled Contributions
Regular contribution schedules are applied automatically to the current strategy, supporting a consistent investing habit without recurring manual input.
Allocation and risk management, explained step by step
Rules-based weighting
Each asset's weight in a portfolio is determined by a fixed set of criteria applied consistently, rather than being adjusted on a case-by-case basis.
Defined risk bands
Every strategy operates within stated risk parameters. When market movement pushes a portfolio outside those bands, the system flags it for rebalancing.
Backtest-first changes
Adjustments to an allocation model are backtested against historical data before being applied, so changes are grounded in past performance evidence.
Full change history
Every adjustment — allocation shift, rebalance, or contribution — is timestamped and retained, giving you a complete record of how your portfolio evolved.
Features designed to fit around a full calendar
AuraxAI is built for people who want a disciplined investing approach without dedicating hours each week to research and monitoring.
Set-and-review cadence
Once a strategy is configured, ongoing management runs on a defined schedule. Review checkpoints are set at intervals you choose, not on-demand monitoring.
Threshold alerts
Notifications are sent when a portfolio crosses a pre-set risk or performance threshold, so attention is only required when something material occurs.
Single-view dashboard
Allocation, performance history, and pending actions are consolidated into one dashboard, avoiding the need to cross-reference multiple sources.
Feature-specific questions
How often is data refreshed?
Data ingestion runs on a set automated schedule so allocation and reporting figures reflect current inputs without manual updates.
What does "backtested" actually mean here?
It means an allocation approach has been run against historical market data to observe how it would have performed under past conditions, before being applied going forward. Past performance is not a guarantee of future results.
Can I adjust the risk bands myself?
Risk parameters are set as part of your strategy configuration and can be reviewed and updated during scheduled check-ins.
Is rebalancing automatic or does it need my approval?
Rebalancing follows the rules defined in your strategy setup. The specific approval workflow depends on the configuration you choose when setting up your account.
See these features applied to a real portfolio setup
General information only — not personal financial advice. Consider your own circumstances or seek independent advice before investing.