RijksLedger AI dashboard that merges data from multiple platforms into one overview

One overview for all your sources of income and investments

RijksLedger AI combines data from multiple platforms and exchanges into one coherent dashboard, so that you can see more quickly where adjustments are needed and which opportunities you can best focus on.

The dashboard shows current positions, revenue streams and risk indicators side by side, instead of spread across separate apps and exports.

Scattered data leads to slow and uncertain decisions

Anyone who is active on multiple platforms — as an additional earner in the gig economy or as a small-scale investor on various stock exchanges — quickly collects data in too many places. Each source has its own structure, its own export format and its own rhythm of updates.

The result is that important signals are noticed late or not at all, and decisions are often made based on gut feeling rather than a complete picture.

  • Data from different apps and exchanges must be merged manually.
  • Trends only become visible after the time to trade has already passed.
  • Risks on individual positions are clear, but the overall picture is missing.
  • Time spent on data collection cannot be spent on actual decisions.
RijksLedger AI analyzes data from multiple sources for a clear decision-making process

One dashboard, fed by multiple data sources

RijksLedger AI connects to the platforms and exchanges you already use and processes that data into actionable, predictive insights. This way, the complexity of multiple systems remains behind the scenes, and you keep an overview.

Multi-exchange link

Connect multiple exchanges and platforms at the same time, without having to switch between separate login environments.

Uniform dashboard

All relevant figures brought together in one view, structured by income, expenses, positions and risk.

Predictive analytics

Models that recognize patterns in historical and current data and translate them into concrete points of interest.

From raw data to substantiated advice

The analysis process follows a fixed, repeatable structure. This makes the outcome imitable, even when the underlying data is complex.

1

Data intake

Data from linked platforms and fairs are collected and read in a standardized way.

2

Predictive modeling

Historical patterns and current signals are combined to estimate likely developments.

3

Risk assessment

Each estimate is compared against known risk factors, so that opportunities are not shown separately from possible disadvantages.

4

Strategic outcome

The results are translated into a concise recommendation, with the underlying reasoning made clear.

Built for extra earners and small-scale investors

Earn extra via multiple platforms

Those who are active on multiple gig platforms often see income coming in at different times and in different overviews. RijksLedger AI brings these flows together, so that it becomes clear which platforms contribute structurally and which mainly cost time.

One weekly overview
instead of separate exports per platform

Spread in small-scale investments

For investors who hold positions on multiple exchanges, diversification only makes sense if the total risk is visible. The dashboard shows positions per stock exchange next to an aggregated risk picture, so that over-concentration is more quickly noticed.

One risk image
across all linked exchanges

Transparency about data and analysis

How does RijksLedger AI handle the security of linked data?

Data from linked platforms and exchanges is processed encrypted and used exclusively for analysis within your own dashboard. Access to raw source data is limited to the systems required for processing.

On what basis are recommendations given?

Recommendations arise from models that combine historical patterns with current market signals. The underlying factors, such as volatility or income dispersion, are explained with each recommendation.

Does the platform work with any exchange or platform?

RijksLedger AI supports a growing number of commonly used exchanges and platforms. When linking a new source, it is first checked whether the data structure is compatible with the analysis models.

Can I decide for myself how much risk counts in the advice?

Yes, the risk weighting can be adjusted to your own preference, from conservative to more risk-accepting, after which the recommendations are recalculated accordingly.

All analyzes are based on data sources linked by you. RijksLedger AI does not fill in missing data with assumptions that do not follow from your own data.

Start structuring your data flows

Connect your platforms and exchanges, and immediately view within the dashboard which patterns are relevant for your next decision.

Start optimizing