Kiziru Lebire consolidates data from your accounts into a single dashboard and uses predictive models to evaluate opportunities for smart capital allocation — without the need to monitor each exchange separately.
For a courier who trades on three exchanges between shifts, or for a freelance analyst managing his own portfolio in addition to his main job, manually comparing prices and transaction history is time-consuming. Each platform has its own interface, its own data export and its own fee logic.
The result is decision-making based on an incomplete picture — a table in one window, a graph in another, notifications on a mobile phone. Kiziru Lebire puts this image together and converts it into one consistent layer that can be worked with systematically.
Illustrative comparison of the typical time consumption of individual steps, not a measured statistic of a specific user.
The platform connects the APIs of individual exchanges, normalizes data formats and evaluates them against historical patterns. The output is not promises, but probabilistically weighted scenarios that the user confirms to himself.
Balances, open positions and transaction history from all connected exchanges on one screen, updated in real time.
The algorithm compares current market conditions with historical patterns and estimates the probability of individual development scenarios.
The system monitors the differences between exchanges and warns if the price difference goes outside the usual range.
Capital allocation recommendations consider historical volatility and current exposure across accounts, not just the spot price.
The model is not based on a single data source. It combines historical price series, trading volume and the frequency of deviations between exchanges to estimate how similar situations have played out in the past. The output is a range of likely scenarios, not an unequivocal prediction.
The user sees not only the recommendation, but also what inputs it is based on — allowing them to assess whether it matches their own risk tolerance.
Connection to API exchanges and aggregation of price and volume data in a uniform format.
An assessment of the volatility, liquidity and historical reliability of a given asset pair.
The model will propose a distribution of capital corresponding to the chosen level of risk tolerance.
The results are compared with the actual development and the model is continuously fine-tuned accordingly.
Risk minimization in practice it does not mean its removal. It means clearly naming the risk the user is taking and the tools he can use to limit it — for example, limits on exposure to one exchange or one asset.
A courier or driver with irregular working hours connects accounts from three exchanges into one dashboard. Instead of checking each application separately during the break, it receives a daily summary and alerts only when there is a relevant deviation.
The freelance analyst sets a rule according to which part of the monthly surplus is automatically included in the allocation proposal. The predictive model shows him how similar decisions have behaved in past periods before confirming, and leaves the final decision up to him.
Kiziru Lebire does not substitute user judgment and does not place trades on its own. It provides a consolidated view of data and recommendations based on the model — the final decision rests with the user, as does the responsibility for its outcome.
The platform is built for people who treat side income as a long-term activity in addition to their main job, and therefore need an overview that can be checked in a few minutes a day.
The platform works with API keys with limited read-only permissions, if the exchange allows it. Keys with the right to withdraw funds are not required and it is recommended not to set them.
Commonly used exchanges with a publicly available API are supported. Linking the account itself usually takes a few minutes, full synchronization of historical data takes a little longer depending on the volume of transactions.
Kiziru Lebire displays the fee structure of individual exchanges as the user himself set it in his account. The platform does not interfere in any way with payments or transfers of funds.
Recommendations can be rejected or modified at any time. The model does not propose a single correct solution, but a range of scenarios with an estimated probability — the final choice is always up to the user.
Trying out the platform does not require moving funds or committing to a long-term subscription. Just link your first account and see what a consolidated view of your data looks like.