A global CPG leader leveraged AI-driven predictive analytics to enhance product offerings, reduce inventory waste, increase revenue, and improve customer satisfaction, all within an efficient eight-week rollout.
A leading insurer harnessed AI-driven predictive analytics to reduce the number of churned clients. This was accomplished by first generating a list of returning clients. After which, sales and marketing efforts targeted these clients. The predictive model was ready for deployment in less than two weeks.
A leading mobile carrier benefited from AI-driven predictive analytics to determine which QA tests will have a high rate of defects along with reasons. Employees were directed to fix such faults before they occur. It took just under a month to build a predictive model that was ready for deployment.
Qualitest’s AI solution helped an IC manufacturer predict failures, optimize root cause analysis, and improve product quality, boosting yield and efficiency with automated, no-code modeling.
A nationwide electricity provider faced a challenge to ensure high service SLA for electric power distribution while increasing technical teams’ productivity. The company’s transformers are located in various locations. Keeping the transformers in optimal health was a costly task as technical teams were responding to infrastructure failures as they occurred.
Qualitest provided telecom company with a sophisticated predictive model solution that increased sales and ROI for digital marketing. The solution proved to be accurate, efficient, and powerful, increasing sales by enhancing the effectiveness of sales calls.
Qualitest empowered financial institutions to swiftly build stable, high-performing options trading models with its no-code ML solution. By leveraging over 40 algorithms, rapid deployment, and minimized risks, we accelerated revenue growth.
Synthetic data is transforming data management by offering a powerful, privacy-friendly alternative to real-world data, facilitating innovation, data security, and scalable, customized solutions to simplify information handling & analysis.
Performance problems that escaped testing and need to be corrected in upcoming releases can be identified using different key performance indicators (KPIs) in the field. To improve performance, developers can get more detailed feedback by capturing and assessing end-user sentiment. In this white paper, you will learn how to gain real-time feedback to help with troubleshooting in the development process, how to capture end-user sentiment and the technical implementation of large language models (LLM's).
