Decision Engine
Decision Engines or sometimes called Decision Support Systems are AI-based systems that enhance the ability of organizations to make smart decisions by training AI models on large amounts of data. These systems help decision makers make informed and quick decisions based on previous cases that they have been trained on.
Thanks to AI-powered predictive capabilities, these systems have the ability to predict future problems before they occur and thus make decisions that help avoid these problems.
Possible use cases
Financial Sector
Developing decision-making engines to assist banks and financial institutions in making investment or credit decisions by analyzing economic trends and predicting financial risks.
Health Sector
Develop decision-making engines to support physicians in making treatment decisions by analyzing medical data and predicting patient cases based on their health records.
Human Resources
Develop decision-making engines to make informed hiring decisions through data analysis and needs identification, which helps in selecting the ideal candidates for the jobs.
Transport Sector
Developing decision-making engines to manage traffic, improve vehicle flow, and reduce congestion. Real-time data is collected and analyzed from cameras and sensors to predict traffic jams and provide instant recommendations for traffic rerouting.
Benefits gained from the development and use of decision-making engines
Make quick and accurate decisions
By providing real, data-driven recommendations, decision-makers can respond faster to changes that occur in the work environment.
Predicting risks and opportunities
Decision-making engines use predictive models to detect future opportunities and risks, helping to make proactive decisions.
Organization-by-organization analysis
Decision-making systems have analytical capabilities that are tailored to the nature and goals of the organization, allowing us to provide customized solutions for each case.