The Challenge
A healthcare organization struggled with their CAPA (Corrective and Preventive Action) investigation process, which was time-consuming, inconsistent, and prone to human bias. Manual root cause analysis was leading to delayed responses and potentially missed underlying issues in their quality management system.
They needed a solution that could standardize and accelerate their investigation process while improving the accuracy of root cause identification.
Our Solution
85%
Reduction in investigation time
Increased
Accuracy in root cause identification
Consistent
And thorough documentation
Enhanced
Compliance with regulatory standards
We developed an AI-powered system to automate and streamline the CAPA investigation process, focusing on sophisticated root cause analysis and pattern recognition.
Project Insights
Key Features
Problem description analysis using the 5W+2H framework
Root cause identification through Ishikawa diagram mapping
5 Whys analysis with intelligent questioning
Corrective action recommendation generation
Technical Architecture
Natural Language Processing for problem analysis
Machine learning for pattern recognition
Automated documentation and tracking
Integration with existing QMS systems
