Use cases

On Time In-Full (OTIF) reporting is essential for measuring the efficiency and reliability of a supply chain. As an important key performance metric (KPI) in this field, it directly impacts customer satisfaction, inventory management, and overall operational efficiency.

Employability scoring for recruitment involves the use of machine learning algorithms to predict the likelihood of job candidates being successfully matched with available positions.

To achieve higher contract fulfillment rates, we used a detection model that automatically sends alerts to streamline the process of managing contract discrepancies.

Ensuring accurate treasury forecasts is crucial for any business, as it directly impacts financial planning, liquidity management, and risk mitigation strategies.

Demand forecasting is the process of predicting future customer demand for a product or service based on historical data, market trends, and other relevant factors.

Predictive maintenance is a proactive approach to maintenance that uses data science and AI algorithms to predict equipment failures before they occur.

Propensity scoring can be used to determine the likelihood of a customer buying, up-selling or churning.

Lead scoring is a methodology used by sales and marketing to rank and prioritize potential customers (leads) based on their likelihood of converting into paying customers.

Churn prediction is a process of identifying and predicting the likelihood of customers or subscribers discontinuing their relationship with a business.