Unleash data-driven insights for enhanced product quality. By analyzing claims, returns, and repairs, businesses gain valuable intelligence on product quality issues, failure rates, and areas for improvement, empowering them to proactively take corrective actions, elevate product quality, and effectively minimize post-sales costs.
Vendor
Tavant
Company Website
Advanced analytics for superior service quality
Empowering businesses with advanced quality analytics solutions
Tavant’s Quality.AI leverages advanced analytics techniques to provide valuable insights and early warning signals for ensuring service quality. By analyzing various quality metrics such as Weibull, survival, defect, and part failure analysis, this solution can identify machine failure clusters and predict potential quality issues. This proactive approach allows companies to take preventive measures and minimize the risk of recalls and returns. With its comprehensive analytics capabilities, our Quality.AI solution empowers businesses to optimize their operations, enhance product quality, and maintain customer satisfaction.
Features
Root cause analysis
AI-enabled 8D problem-solving templates for 5-why analysis, Ishikawa/Fishbone diagrams, and fault tree analysis.
Key metrics
Identify key metrics such as cost of quality, yield rate, audit score, scrape rate, MTTR, MTBF, variances, supplier score card, and reliability growth rate.
Recalls and returns analysis
Leverage APIs to connect with external systems and get proactive alerts, including those for customer dissatisfaction results and quality issues.
Quality prediction
Leverage predictive models that forecast future quality issues or trends and supplier data for risk modeling and optimization.
Early warning signals
Collect, find, and alert product quality issues by combing data from warranty, work orders, cases, product usage, and IoT sensors.
Profitability analysis
AI-enabled defect detection leverages computer vision and deep learning models help identify defects in components.
Quality control
AI models help analyze, run inspection tests, and audits for defect analysis, statistical process control, FEMA and Pareto analysis.
Reliability analytics
Use custom ML models to evaluate system reliability using Weibull, scale analysis, and defect and part failure analytics.
Benefits
Real-time insights
Enable businesses to make proactive and immediate decisions based on the most up-to-date information
Industry specific expertise
Enable standardization and exponentially reduce data engineering investments
Advanced predictive capabilities
Utilize ML models to forecast future trends, anomalies, or potential issues based on historical and real-time data
Wide choice AI models
Various AI models that seamlessly and securely run on your data and store insights in your subscription
APIs that offer flexibility
APIs to build or run solution analytics, reports, and dashboards