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Navlik Sivren Dashboard view of a data-based analysis interface for investors
AI-powered investment analysis

Intelligence instead of guesswork

Navlik Sivren combines historical market data with back-tested AI models and translates them into understandable recommendations for action - so that even first-time investors can make well-founded decisions without being an analyst themselves.

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Ø 2010–2023
Period of backtest scenarios
24/7
continuous data evaluation
3 steps
from raw data to recommendation
Methodology

This is how a recommendation is created

Every assessment by Navlik Sivren goes through the same comprehensible process - from data collection to the concrete, understandable option for action.

01

Data aggregation

Price, volume and macro data from numerous sources are continuously merged and cleaned before being incorporated into the models.

02

AI analysis & backtesting

Models are tested on historical market phases before they are used productively - this shows how a strategy would have reacted in past ups and downs.

03

Understandable insight

The model results produce a compact recommendation with justification, risk assessment and time horizon - without any technical jargon.

Results & Simulation

What back-tested strategies show

The following comparisons come from historical simulations based on past market data. They describe how an approach would have performed in the past - not a promise of future results.

criterion Traditional approach AI-powered analysis
Reaction to market movements Delayed, often emotionally influenced Rules-based, continually updated
Database per decision Individual key figures, news situation Broad historical data sets and patterns
Traceability Depending on individual assessment Documented backtest history
Consistency over time Fluctuates with daily form and mood Consistent methodology

Basis: simulated application of the models to historical market cycles. Past simulation results are not an indicator of future performance.

Risk management

Risk minimization

In backtests, the portfolio weighting adjusts to measured fluctuation ranges in order to cushion extreme fluctuations - instead of rigidly sticking to an allocation.

Return

Optimized return

The models give greater weight to historically stable patterns than short-term fluctuations and aim for a balanced course over several market cycles.

Real-time analysis

Processing speed

New market data is continuously imported and converted into updated assessments several times a day, instead of only being checked once a quarter.

Navlik Sivren team evaluating market and analysis data
About Navlik Sivren

A tool for making decisions, not a replacement for them

Navlik Sivren was designed to give people with capital but no specialized training in portfolio management the same access to structured analysis that institutional investors have used for years.

The platform does not replace your own decision. It provides a comprehensible, data-based basis - prepared in such a way that it is understandable even without a finance degree.

Use cases

What situations Navlik Sivren is intended for

Three typical starting points for first-time investors - and how data-based analysis supports this.

Security through data

Diversify your portfolio without getting bogged down

Those who invest for the first time often distribute capital based on their feelings. Navlik Sivren uses historical correlations to show how asset classes have behaved independently of each other and suggests a diversification that fits individual risk appetite.

3-5 classes
typical spread framework depending on the risk profile
ongoing
Checking the weighting based on new data
Security through data

Stay calm during market volatility

Price declines trigger hasty selling among many first-time investors. The AI ​​evaluates fluctuations in the context of historical patterns and distinguishes between short-term noise and actual changed conditions - without an emotional reaction.

24/7
Observation without emotional distortion
Sample check
Classification of current movements in historical context
Security through data

Plan long-term wealth creation

Instead of chasing short-term trends, the models are based on periods of several years. Recommendations are checked regularly, but are not adjusted with every daily fluctuation - for calmer, predictable wealth accumulation.

Multi-year horizon
Alignment of the core strategy
Regularly
planned review instead of daily reaction
Transparency

Frequently asked questions about data, model and costs

Direct answers to the questions first-time investors ask us most often.

How does Navlik Sivren handle my data?

Market and portfolio data are processed for the analysis, not sensitive personal information that is not necessary for the recommendation. Details on storage and deletion can be found in our data protection declaration.

Can I understand how a recommendation is created?

Each recommendation is justified by the underlying factors and the historical backtest result. You see what assumptions are being made instead of just getting a result without context.

Does the platform replace your own investment decision?

No. Navlik Sivren provides a structured basis for decision-making. The final decision – whether, when and to what extent to invest – remains with you.

How is the cost structure structured?

The exact conditions depend on the scope of use and will be explained to you transparently before you register, without any hidden additional fees afterwards.

Invest smarter now

A basis for decision-making that is based on back-tested models instead of gut feeling - prepared in an understandable way for you to start investing.

  • Recommendations based on back-tested, historically verified models
  • Ongoing reassessment instead of a one-time snapshot
  • Understandable justification instead of just a flood of key figures
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