Nyzaloris data analyst reviewing portfolio strategy data in a calm, professional workspace

Decisive intelligence for crypto portfolios, verified in the open

Nyzaloris analyses market data continuously and acts on it through a disciplined, rules-based process. Every strategic decision is recorded in community-verified performance logs, so clients can review the reasoning behind each adjustment rather than take it on faith.

A public record of every strategic decision

Scepticism towards unverified performance claims is well-founded in this market. Nyzaloris addresses it directly: each adjustment our models make to a modelled portfolio is time-stamped and published to a public ledger, independent of our own marketing materials.

Audit method Decisions are logged with the data inputs that triggered them, the model's confidence score, and the resulting action. Logs are retained in full, including instances where the model's position was later reversed.

This record allows clients and independent reviewers to assess consistency over time, rather than relying on cherry-picked outcomes.

Review the public performance logs →
Nyzaloris analyst examining performance log data on a desktop screen

Three functions behind every recommendation

The predictive engine is built around three coordinated functions. None operates in isolation; each informs the others before a recommendation is issued.

Monitoring

Real-time volatility monitoring

Tracks price movement, order book depth, and liquidity shifts across major exchanges, flagging conditions that fall outside normal statistical ranges.

Risk Management

Automated risk-parity adjustments

Rebalances exposure across assets so that no single holding dominates portfolio risk, adjusting weightings as correlations between assets change.

Forecasting

Predictive trend modelling

Combines historical pattern analysis with current market structure to estimate the probability of sustained directional moves, not short-term noise.

How a recommendation is reached

Strategic oversight remains with a human governance team at every stage. The model proposes; a defined set of rules and periodic human review determine what is acted upon.

  1. Data ingestion

    Market feeds, on-chain activity, and macroeconomic indicators are collected continuously and normalised into a common format before any analysis begins.

  2. Model validation

    Signals are filtered against historical false-positive rates. Low-confidence signals are discarded rather than acted upon, reducing exposure to short-lived noise.

  3. Execution strategy

    Validated signals are translated into position adjustments sized according to pre-set risk limits, then logged publicly at the point of execution.

Strategy Health Index — an illustrative view

Rather than quote a headline return figure, Nyzaloris publishes a Strategy Health Index: a composite measure of how closely a strategy's recent behaviour matches its intended risk and volatility profile.

Strategy Health Index — rolling 90-day view

Solid line: realised Strategy Health Index. Dashed line: pre-set target band. Figures are drawn directly from the public performance logs and updated on each logged decision.

Past performance, including the Strategy Health Index shown above, is not indicative of future results. Cryptoasset values are volatile and capital is at risk.

Technical and safety considerations

How is client capital secured?

Nyzaloris offers a non-custodial configuration by default: strategy instructions are transmitted to a client's own exchange account via scoped API keys that permit trading but not withdrawal. Clients retain direct control of their holdings at all times.

What happens to liquidity during periods of high volatility?

Position sizing accounts for order book depth at the time of execution. In thin markets, the model reduces trade size or delays execution rather than forcing a fill, which is logged as an explicit decision in the public record.

How much discretion does the AI model actually have?

The model generates recommendations within fixed risk parameters set by the governance team. It cannot exceed pre-set exposure limits, and any change to those limits requires manual review before deployment.

Review the data before you decide

The public performance logs are open to anyone, with no commitment required. Read the methodology, examine the logged decisions, and judge the consistency for yourself.

Access Performance Logs