Deriv Pilot brings multi-exchange support and unified intelligence into a single working view, so your decisions rest on complete information rather than scattered, delayed fragments.
What you see on day one: a consolidated dashboard pulling live positions, liquidity, and risk markers from each connected exchange into one timeline, with model-generated notes attached to the events that matter.
Most professionals managing positions across several exchanges rely on a patchwork of browser tabs, exported spreadsheets, and alerts that arrive after the moment has passed. Each source is accurate on its own, but none of them talk to each other, and the gaps between them are exactly where risk accumulates.
Deriv Pilot was built around a simple observation: the edge is rarely missing data, it is unreconciled data. Bringing every feed into one coherent timeline is what turns noise back into a usable signal.
Positions and order books live on separate exchange dashboards, each with its own refresh rate and interface.
Manual cross-referencing takes minutes that volatile markets do not reliably give back.
A single number, such as spread or depth, means something different on each venue, making like-for-like comparison error-prone by hand.
Reconciling five dashboards before every decision leaves less attention for the decision itself.
Deriv Pilot connects to each of your exchange accounts through read-oriented integrations and reconciles the feeds in real time, so figures that previously lived in separate tabs are shown side by side, on the same timeline, in the same units.
Feeds from connected exchanges are refreshed continuously rather than on a fixed polling schedule, reducing the lag between an event and its appearance in your view.
Depth and spread figures from each venue are merged into one comparable picture, making it easier to judge where execution conditions are currently favourable.
Pattern analysis runs across the combined dataset rather than per exchange, so correlations between venues can be surfaced rather than missed.
Thresholds can be set per asset or per venue, with notifications routed to a single inbox instead of several separate exchange apps.
Deriv Pilot is deliberately built as a decision-support layer. The models surface patterns and quantify likely outcomes; the final call, including sizing and timing, remains with the person using the platform.
This design choice reflects a practical limit of any predictive system: markets change regime, and a model that is not open about its own uncertainty can mislead more than it helps. Deriv Pilot shows its confidence levels alongside every recommendation, rather than presenting a single number as certainty.
Account-level feeds from each connected exchange are pulled continuously and normalised into a shared schema, so comparable fields line up regardless of source formatting.
Statistical and machine-learning models trained on historical and live cross-exchange patterns generate short- and medium-horizon probability estimates for the scenarios you are tracking.
Outputs are weighted against position size, concentration, and correlation across your connected accounts, highlighting where exposure is building before it becomes a problem.
Recommendations are translated into specific, reviewable suggestions, for example an entry window or a hedge ratio, with the reasoning behind each one available on request.
The scenarios below describe realistic working patterns among Deriv Pilot users who manage positions across several exchanges alongside other professional responsibilities.
A retail investor holding positions across four exchanges used the unified dashboard to spot that two of their largest holdings were more correlated than the separate account views suggested. Rebalancing based on this combined picture reduced portfolio drawdown by 15% over the following quarter.
Reduced drawdown by 15%A strategic lead evaluating a new position used the cross-platform model to identify high-probability entry points appearing simultaneously across four exchanges, rather than waiting to confirm the pattern on a single venue first.
Entry points confirmed across 4 exchanges simultaneouslyAn investor managing income from several trading accounts used the aggregated liquidity view to size a hedge against total exposure rather than per-exchange exposure, avoiding the over-hedging that had occurred under the previous manual process.
Hedge sized against true combined exposureFor users based in Germany and across the EU, data handling and model reliability are treated as core product requirements, not afterthoughts.
Exchange connections use read-oriented API access wherever the venue supports it, and credentials are encrypted at rest and in transit. Access to account-level data within Deriv Pilot is scoped and logged, so activity can be reviewed if needed.
Personal and account data is processed in line with applicable EU data protection requirements, including defined retention periods and the ability to request access to, or deletion of, stored data. Data is not sold or shared with third parties for advertising purposes.
Every model output is shown with an associated confidence range rather than as a single definitive figure. Historical performance of each model is reviewed on a rolling basis, and material changes to a model's behaviour are communicated to users before they take effect, not after.
Connecting your first exchange takes a few minutes and does not require moving funds or closing existing accounts elsewhere. You can review the unified dashboard on your own data before deciding how much of your workflow to shift across.
Get StartedNo fabricated promises, no locked-in contracts at sign-up: you connect one exchange, review the output, and decide from there.