AI algorithms analyze 500 companies weekly to find the best opportunities with solid fundamentals and attractive prices
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Advanced algorithms for pattern recognition and trend analysis in financial data.
Predictive models that anticipate market movements based on historical and current data.
Access weekly reports with investment opportunities across multiple markets.
A systematic and automated process that analyzes the market for you
We analyze all the companies of the S&P 500 every week in an automated way
We filter by financial health and signs of undervaluation
Our ML model identifies early recovery opportunities
You receive detailed analysis every Saturday in your email and access all weekly and historical recommendations in your dashboard
Systematic analysis without emotions. While other investors are swayed by news and market panic, our system identifies opportunities based solely on data and financial fundamentals.
Real examples of recommendations that have generated significant returns in short periods
Past results do not guarantee future returns. Investments carry risks and may result in losses.
Every Saturday you'll receive an email with detailed analysis like this
Technology Sector Company
Every Saturday you receive the main recommendation directly in your inbox
Access all recommendations anytime from your control panel
This is just a historical example.
Sign up for free and receive this week's recommendation in your email every Saturday.
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Legal Notice: AI-generated analysis. This content is informative and does not constitute financial advice. Recommendations are based on rigorous fundamental analysis. Always do your own research before making investment decisions. All investments carry risks and may result in losses.
Detailed Analysis of each investment opportunity
Automated Selection by Zignolz algorithms
Weekly Delivery directly in the subscribers' private area
No commitment · Cancel anytime
Systematic data-driven analysis, not market emotions
S&P 500 companies analyzed
Financial health and key metrics
Identifies recovery patterns
Best undervalued opportunities
Let the data work for you
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Everything you need to know about Zignolz
Our recommendations are based on a machine learning model that analyzes multiple factors: financial health, undervaluation signals, and historical recovery patterns. However, no investment recommendation is 100% safe. We provide data-based analysis so you can make informed decisions, but the market always carries risks.
Our system follows a 4-stage process: (1) Weekly analysis of the 500 companies in the S&P 500, (2) Filtering by financial health and price drop signals, (3) ML identification of patterns that historically precede recoveries, and (4) Selection of the best opportunities with solid fundamentals. We focus on companies undervalu, not on speculation.
Each weekly recommendation includes: the stock ticker, fundamental reasons for the recommendation, key financial metrics, analysis of current price vs. intrinsic value, model confidence level, and sector context. We also include historical charts and suggested entry points.
You don't need to be an expert. Our analyses are designed to be clear and actionable. However, we recommend having basic knowledge about how to buy stocks and understanding that all investments carry risks. Never invest money you can't afford to lose.
Yes, you can cancel your subscription at any time from your dashboard. There are no long-term contracts or penalties. If you cancel, you will retain access until the end of your current billing period.
Yes. We offer a free plan that allows you to receive 1 weekly recommendation without needing a credit card. This lets you test the quality of our analyses before committing to a paid plan.
We currently focus exclusively on the S&P 500, which includes the 500 largest and most liquid companies in the United States. This focus allows us to maintain maximum quality in our analysis and ensure that recommended stocks are easily accessible to any investor. However, we have several models that we are developing and refining, and in the future they will be available to offer analysis of more markets and recommendation systems.
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