Shield unifies fragmented streams of market data into a single view and applies predictive models to support incremental income decisions with more clearly calculated risk.
Gig economy participants and individual investors typically track more than one source of data—individual platforms, exchanges, or apps—with no common format for comparison. Decisions are made under pressure and often based on an incomplete picture.
The result is rarely a lack of information. More often, it's an excess of unrelated signals that slows down a response just when it's most needed.
The process is designed to be explainable, not to be presented as foolproof. Each step is verifiable and the results carry a marked confidence interval.
Connect to multiple exchanges in parallel via their APIs, without the need to switch between separate applications to check each source.
Indicators from different exchanges are presented in a uniform format, arranged by risk priority, not in order of entry.
Forecast intervals based on historical series and current volatility, with a separate marking for low certainty in sharp market changes.
Quantitative assessment of exposure in each scenario, including when combining income from several sources at the same time.
Data is refreshed at fixed intervals suitable for decision-making without being overwhelmed by every micro-change in price.
Filter by exchange, time range and risk category to see only relevant information for the current decision.
When income depends on several platforms with different fees and payout schedules, a single dashboard shows the workload and expected net worth for a given period in parallel.
For an investor holding positions on multiple exchanges, Shield aggregates the data to show overall risk exposure, rather than looking at each exchange individually.
Before diverting time or capital from one source to another, the model assesses how the change would affect overall income stability under different market conditions.
Data is retrieved through each exchange's public APIs, normalized and stored with a timestamp. No automated trading is done — the analysis is an information layer on top of your own accounts.
Synchronization takes place at fixed intervals based on the type of asset and the workload of the respective exchange. For slower sources, the interval is explicitly noted on the board to avoid a misleading sense of timeliness.
Models publish an uncertainty interval with each prediction, not just a single value. The historical deviation between forecast and actual result is tracked periodically and is visible in the methodology section of the dashboard.
The linked exchanges are accessed with limited read rights, without permission to withdraw funds. Identification data is encrypted at storage and not shared with third parties.
In the event of a temporary disconnection, the corresponding dashboard row is marked as out of date instead of displaying the last known value without context. Analysis continues with available sources.
Connect available exchanges, set an analysis horizon, and review the estimated risk interval before committing time or capital.