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Eik Kapitveste — data screens with market analysis and risk indicators
AI analysis platform · NL

Quantitative analysis for a lower-risk entry into crypto

Eik Kapitveste combines quantitative modeling with military-grade encryption, so you can inform investment decisions with data instead of market sentiment.

The platform is designed for students and starters with limited capital who seek a structured, documented method instead of speculative trading.

Start Analysis Built within the framework of GDPR and Dutch financial regulations
Security & methodology

Where analytics and security meet

The platform's recommendations are only useful if the underlying infrastructure is reliable. Therefore, both components are specified separately below.

  • Encryption (rest)AES-256
  • Encryption (transport)TLS 1.3
  • AuthenticationMulti-factor, hardware token
  • Asset storageSegmented cold storage
  • Model typeEnsemble: gradient boosting + time series model
  • Data refreshEvery 15 minutes

Military encryption in practice

All data traffic between your session and our servers is encrypted according to AES-256, the standard that is also used in defense and government infrastructure. Access to account features requires a second authentication factor, independent of your password. Key rotation and access logging are independently monitored for anomalous patterns.

Operation of the predictive model

The model processes historical price series, order book depth and macroeconomic indicators to calculate a risk score per asset. This is a statistical estimate based on available data, not a guarantee of future returns. Each recommendation is accompanied by a confidence interval, so you can consider the uncertainty of the model in your own decision.

Data methodology

From raw market data to a substantiated allocation proposal

Each recommendation goes through three fixed steps. The reasoning behind an advice is therefore always traceable.

STEP 1

Data ingestion

The system collects market data from multiple regulated exchanges, including order book depth, historical volatility and macroeconomic indicators. New data is processed every 15 minutes.

STEP 2

Risk filtering

Assets are screened for liquidity, volatility profile and correlation with the broader portfolio. Assets that do not meet the minimum liquidity threshold are automatically excluded.

STEP 3

Optimization output

The model generates an allocation proposal within the risk profile you set, with an explanation of the underlying factors and a confidence interval per recommendation.

Risk management

AI-supported decisions versus manual speculation

The table shows the structural differences between a model-based approach and an approach that relies solely on individual assessment.

Feature AI-enabled approach Manual speculative approach
Database Quantitative models on historical and current market data Individual assessment, often based on news or sentiment
Risk assessment Continuous recalculation of the risk score per asset Occasional or no structured risk assessment
Diversification Model-based distribution across asset classes and liquidity profiles Depending on individual preference, often one-sided
Emotional bias Limited by fixed, automated rules Higher, due to direct exposure to price fluctuations
Documentation decision Recorded substantiation for each recommendation Often not documented or traceable
Risk score
Scale from 1 to 10, based on volatility, liquidity and correlation with the portfolio.
Volatility index
Standardized measure of price fluctuation over a chosen period, expressed in percentages.
Confidence interval
Bandwidth around a model outcome that reflects the statistical uncertainty of the estimate.
1–3 · Low risk 4–6 · Medium risk 7–10 · High risk
Regulatory Compliance & Security

Designed for the Dutch market

The sections below describe how data, assets, and access are organized within the platform.

Regulatory framework

Eik Kapitveste structures its services within the framework of the GDPR and takes into account the requirements that Dutch and European regulators impose on providers of digital asset services. Customer data is only processed within the EU.

Encryption standards

All data at rest is encrypted with AES-256. Data traffic is secured via TLS 1.3. Access logs are independently monitored for anomalous login patterns and unusual sessions.

Custody protocol

The majority of assets are held in segmented cold storage, separate from operational systems. A limited portion remains in hot wallets for transaction processing, limited by internal limits.

Frequently asked questions

Technical and practical questions

The questions below cover the most frequently asked topics about model accuracy and capital security.

How accurate are the model's predictions?

The model provides a statistical estimate based on historical and current market data, not a guaranteed outcome. Each recommendation is accompanied by a confidence interval, so that the uncertainty of the estimate is transparent. Markets can develop differently than the model indicates.

What happens to my data?

Data is processed within the EU, stored encrypted according to AES-256 and used exclusively for the operation of the analysis platform. Processing takes place within the framework of the GDPR.

Can I adjust my risk profile?

Yes. You set a risk limit in advance; the model generates allocation proposals that fall within that limit. Adjustments will be included in the next data refresh.

Is my capital insured against loss?

No. Crypto investments always involve market risk and there is no guarantee against decline in value. The model limits exposure to illiquid or highly correlated assets, but does not eliminate market risk.

View the technical documentation →

Complete the risk intake and view your dashboard

The intake consists of a few questions about your risk appetite and available capital. Based on this, the model draws up an initial allocation proposal, including substantiation.

System status: operational · last data update: 15 min ago
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