Jaxolith connects to your existing accounts, runs predictive risk modelling on your data, and proposes a diversified allocation you can deploy with one click — built for professionals who need precision without spending their evenings on spreadsheets.
Jaxolith ingests market, account, and macroeconomic data continuously rather than on a fixed schedule. Each feed is normalised and scored against a predictive risk model that flags where return and exposure diverge from your stated tolerance.
The output is not a generic recommendation. It is a ranked set of adjustments, each with a stated confidence level and the data points behind it, so you can see why the model reached its conclusion before you act on it.
There is no manual data entry and no spreadsheet reconciliation. The process is designed to be completed once, then monitored rather than repeated.
Link accounts through encrypted, read-only API integration. Jaxolith never takes custody of funds or execution rights at this stage.
The model runs a risk-parity assessment against your current holdings, identifying concentration and correlation that manual review would take hours to surface.
Review the proposed allocation and confirm it in one action. No further configuration or repeated approvals are required for routine rebalancing.
Each feature exists to shorten the distance between data and a defensible decision.
Continuous monitoring surfaces shifts in exposure as they happen, rather than at the next scheduled review.
The same model logic applies whether you hold a single account or several, giving a consistent strategic edge as your portfolio grows.
Every recommendation is logged with its stated confidence and the result observed afterwards, so performance can be reviewed over time rather than taken on trust.
Institutional-grade intelligence is applied to flag concentration risk early, before it becomes a material drag on returns.
We publish how the system works rather than relying on endorsements. The logic behind each recommendation is available for review within the platform.
Our predictive models combine time-series forecasting with risk-parity logic, weighting each data source by its historical reliability rather than treating all inputs equally. When confidence falls below a set threshold, the system withholds a recommendation rather than guessing.
Every model update is version-controlled and tested against historical data before deployment, so changes in behaviour can be traced to a specific release rather than appearing without explanation.
Account data is processed solely to generate your recommendations and is not sold or shared with third parties for marketing purposes. Data handling follows UK data protection requirements, and you can request a full export or deletion of your data at any time.
Connect your accounts and receive your first set of model-backed recommendations before you finish your coffee. No manual spreadsheets, no lengthy onboarding call.
Start in under 60 seconds Setup is self-service and typically completed in under a minute.