case study

Redefining trading with AI automation

We developed Viallion to transform manual trading strategies into intelligent, data-driven workflows through AI-powered automation.

The result: faster execution, reduced emotional bias, and consistent, scalable performance across investment teams.

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About Viallion

Viallion is an advanced AI-powered trading automation platform, designed to optimize sophisticated investment strategies. Developed in collaboration between traders and industry experts, its purpose is to transform manual processes into precise and controlled algorithmic execution.

This platform is positioned as an essential tool for investment teams seeking to handle large volumes of market data and execute trades in real-time, minimizing emotional bias and maximizing consistency and scalability.

The starting point

In a dynamic and often unpredictable market environment, investment teams face the challenge of maintaining consistency, control, and adaptability. Manual trading strategies are prone to emotional biases, operational inefficiencies, and scalability limitations, making it difficult to optimize performance and ensure traceability.

A solution was needed to help teams evolve their approach, replacing manual processes with data-driven execution and intelligent automation, while ensuring comprehensive traceability and control.

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THE GOAL

Bringing discipline and scale to trading operations

Our goal was to empower portfolio managers with a platform that turns high-level investment ideas into disciplined, algorithmic execution—enabling faster iteration, reduced operational burden, and better performance across strategies.

Viallion

What we did

Developed within the Making Sense Innovation Lab, Viallion was built as a robust platform with a three-step automation engine designed to transform trading strategies into a fully operational, AI-driven solution. This innovation-focused approach ensured the platform could deliver consistent results in real-world investment environments.

Combining quantitative models, technical analysis, and AI optimization, the system streamlined strategy creation, automated execution, and enabled continuous performance improvement based on key financial metrics.

The three-step automation engine included:

  • Strategy development: Expert-designed hypotheses, backtested with historical data, using a hybrid of quantitative models, technical analysis, and AI-driven optimization.
  • Intelligent execution: Fully automated trading via broker-integrated systems with AI-tuned parameters for asset-specific performance.
  • Continuous optimization: Ongoing testing of new hypotheses, guided by metrics like Sharpe, Sortino, CAGR, and Win Ratio, deploying only top-performing models.
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Results

Viallion is already operational in live investment environments , demonstrating its ability to operate under market pressure, adapt to volatility, and support professional-grade decision-making.

Consistent performance: The platform powers Aconcagua Hedge Fund, Making Sense’s proprietary investment vehicle, and is being tested by select private investors, demonstrating consistent performance.

Precise execution: Viallion ensures precise execution and end-to-end traceability, with strong risk control and low volatility.

Reduced biases: It minimizes emotional bias and operational friction by embedding human insight into disciplined, rule-based automation.

Scalability: It enables scalable operations without the need to grow your team

  • We are product builders.
  • We are result accountable.
  • We are strategic partners.
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