Our analytical engine processes market data in real time and transforms its volume and complexity into specific recommendations. The goal is to reduce the decision-making risk of investors and companies, not to replace their judgment.
The process is divided into three steps that can be traced back and verified. No phase is complete without a recorded input and output.
The system continuously collects market and transaction data from publicly available and licensed sources. Ingestion takes place in real time so that recommendations reflect the current state of the market, not a delayed snapshot.
Predictive models look for patterns in volatility and correlations between assets. Each output of the model is supplemented with a degree of certainty that the model attributes to the given result.
The resulting recommendations are formulated as specific steps — not general signals. The user can see what variables the recommendation was based on.
The technical capabilities of the platform are reflected in three areas that are measurable for investors and company management.
Predictive models evaluate the volatility and data integrity of inputs before translating them into recommendations. The risk exposure is thus visible before the decision, not after it.
The processing of large volumes of data, which would take days manually, is automated and continuous. The analyst thus receives processed output, not raw data to browse.
The same analytical basis can be applied to a single investor's portfolio as well as to strategic planning across multiple business units, without the need to build a new model from scratch.
Each recommendation that the platform generates is recorded with a time stamp and subsequently publicly available for review.
| The date | Referral type | Result after 30 days | Condition |
|---|---|---|---|
| 03. 2024 | Portfolio Allocation — Crypto | In line with the prediction | Confirmed |
| 04. 2024 | Reducing exposure — a volatile asset | Deviation outside the predicted range | Tracked |
| 05. 2024 | Diversification — corporate reserves | In line with the prediction | Confirmed |
The log also contains recommendations that deviated from the actual market development. We believe that credibility comes from a willingness to show the less successful periods, not just the profitable ones.
The results can be verified by community members independently of us — by comparing the recorded recommendation with publicly available market data on the same date.
Savaqorilyx was created to offer investors and corporate teams a second, data-driven opinion on capital allocation and strategic planning decisions. Instead of general signals, we provide a breakdown of the variables that go into the recommendations.
The platform is for those who want to verify, not just believe. Therefore, the methodology is described openly and the results can be traced back, including the period when the prediction differed from reality.
The same analytical basis is used differently depending on the type of decision — from crypto-portfolio management to corporate planning.
An investor follows a volatile market and needs a breakdown of risk in real time, not once a week. Savaqorilyx complements its own analysis with modeled prediction and highlights deviations from expected market behavior.
Company management uses the platform as an additional input into decision-making processes — for example, when planning a budget or evaluating new investment opportunities. The recommendation connects to existing reporting, does not require a separate workflow.
More questions can be found on the page FAQ.
Access to the platform does not require a long-term commitment. You can first view the referral model and public log without registration.
Enter the platformThe approach is based on community verification — the results are presented not only by us, but also by those who use them.