AI Quality across industries
TruEra's AI Quality solutions help companies drive model quality and trustworthiness across a broad set of use cases and industries.
Aerospace and Defense
Accelerate innovation and mitigate security risks for consistent mission success.
Develop new products and services, reduce costs, and enhance the client experience, while improving regulatory compliance and reducing fraud.
Leverage AI models to streamline operations, reduce risks, and deliver services to citizens more effectively.
Improve clinical, operational, and financial decisions. Get insights and predictions that improve quality of care or drug and treatment development.
Ensure that models influencing activities such as skills-assessment based job matching or reviewing compensation management are executing effectively. Minimize bias and increase the fairness of HR models.
Easily assess risk, detect fraud, and optimize decisioning and pricing. Stand out with faster, more efficient customer service.
Improve operational effectiveness with predictive maintenance and better demand forecasting. Accelerate new product line setup and extend factory automation.
High Stakes Models
- Asset management
- Algorithmic trading
- Energy investment
- Drug development
When the stakes are high, the ability to thoroughly explain model predictions, provide confidence bounds, and demonstrate model quality is paramount. TruEra provides the confidence you need to drive machine learning.
Human Decision Support
- Sales lead scoring
Machine learning applications that are intended to inform human decisions will struggle to perform if humans can’t understand how the model arrives at its conclusions or if they struggle to collaborate with it. TruEra helps data scientists solve this black-box problem for multiple use cases.
- Predictive maintenance
- Fraud detection
- Demand forecasting
Explainability and model quality are also critical to models that are part of complex business workflows that involve both humans, machines, and complex data inputs. TruEra helps demonstrate model trustworthiness for different use cases.