Platform Cmponent

Quantum Machine Learning (QML)

QDT's Automated Machine Learning Engine

  • User-friendly predictive modeling
  • High-quality data access
  • Customizable AI solutions
  • Industry-wide scalability
  • Rapid actionable insights

The QML Process

Time-Domain Autocorrelation for Predictor Alignment

Understanding and leveraging the temporal relationships between predictors and the target variable is crucial for accurate forecasting. The algorithm employs autocorrelation techniques to identify and utilize these relationships, ensuring that the temporal and causal dynamics of the series are captured

Automated Machine Learning (AutoML)

The core of Quantum ML's prowess lies in its AutoML capabilities, which automate the end-to-end process of applying machine learning to real-world forecasting problems. This includes automatic model selection, feature engineering, model training, and hyperparameter tuning

Bayesian Optimization

A sophisticated technique used for hyperparameter tuning that models the objective function (e.g., model accuracy) and uses this model to select the most promising hyperparameters to evaluate in the true objective function. This approach is efficient and effective for optimizing complex models.

Ensembled Forecast

Multiple models are combined using a Stacking algorithm. This ensemble approach leverages the strengths of individual models while mitigating their weaknesses, leading to improved overall forecast accuracy.

Additionally, models from multiple time frames are integrated, enhancing the robustness of the forecasts by incorporating both short-term and long-term trends.

Applications and Outputs

The algorithm's outputs are multifaceted, offering not just forecasts but also insights into driver importances, the return on investment for media/trade, and optimization pathways for investments. These outputs are visualized in an intuitive manner, allowing users to easily derive actionable insights.

The  algorithm is designed to be universally applicable across any time-series forecasting scenario. This versatility, combined with the algorithm’s sophistication and automation, makes it a powerful tool for a wide range of industries and applications, from sales forecasting in consumer goods to financial market predictions and beyond.

Quantum Data Lake offers a vast, secure collection of data, seamlessly integrating with analytics tools for diverse industry use, driving innovation and efficient decision-making.


Quantum UI, part of the QDT platform, offers an intuitive interface that simplifies complex data analysis with a user-centered design for seamless interaction with extensive data and machine learning capabilities.


Kubernetes-Driven Architecture: Enhancing Machine Learning Scalability and Security