Human Resources

Calligo leverages machine learning to identify key factors impacting employee attrition, enabling organizations to enhance company culture, productivity, and retention while reducing long-term costs.

Calligo utilizes machine learning models to identify employees at risk of leaving and implements targeted strategies to mitigate attrition, preserving profitability, morale, and reducing rehiring costs.

Machine learning optimizes onboarding by identifying factors impacting new hire performance and prescribing resource allocation for cost reduction and improved outcomes.

Calligo utilizes predictive and prescriptive analytics, including competitor salary data, to determine optimal salaries for employees, reducing attrition and controlling company costs while improving performance and revenue.

Calligo’s machine learning solutions enhance the prediction of new hire performance by considering multiple factors, reducing reliance on unreliable interview scores, lowering costs, and providing better categorization of potential candidates through recommended application questions.

Calligo uses employee survey data, evaluations, sales data, and HR data to create predictive models that identify key metrics of employee engagement impacting profitability, while also providing prescriptive solutions to gauge the impact of specific business changes and meaningful survey and evaluation questions.

Calligo utilizes predictive models and time-series analysis to determine how long a position is likely to remain unfilled, enabling cost savings and labor reallocation for improved productivity and team cohesion.