A prominent multi-billion-dollar Molecular Diagnostics company in the San Francisco Bay Area sought to improve their manufacturing efficiency, cycle times, and product quality. They aimed to achieve this by implementing Industry 4.0 practices and integrating Machine Learning (ML) solutions.
We assembled a dedicated team of up to 4 offshore experts to deliver a comprehensive solution
Centralized data lake ingests data from machines, providing a holistic view for informed decision-making.
Custom mobile app allows for instant alerts and proactive actions based on real-time production data.
Intelligent algorithms improve efficiency and quality through anomaly detection, failure prediction, process control, and matching.
User-friendly app with dashboards empowers data-driven insights through descriptive, predictive, and prescriptive analytics.
Over 50% improvement in response time to manufacturing issues due to real-time visibility.
3% reduction in quality-related losses achieved through weld quality prediction using ML.
35% decrease in unscheduled maintenance for the ultrasonic welder, resulting in increased operational uptime.
Faster process development facilitated by variability analysis and correlation models generated through ML.
A healthcare provider sought to leverage artificial intelligence (AI) to enhance diagnostic capabilities for radiologists. They aimed to develop an enterprise-grade software solution utilizing AI algorithms for various radiology applications.
We assembled a dedicated team of up to 4 offshore experts to deliver a comprehensive solution
Developed new algorithms and evaluated/benchmarked existing ones, ensuring optimal performance for mammogram/X-ray analysis.
Designed a cloud app specifically for identifying and classifying tumors in mammogram images, supporting radiologists' diagnoses.
Implemented various cancer risk models as software, generating patient risk scores for informed healthcare decisions.
Created an iPad/web app to streamline patient intake, data collection, and mammography screening, replacing paper methods.
The developed solutions achieved an impressive accuracy rate exceeding 85%, aiding in more reliable diagnoses.
The patient intake process was streamlined, reducing wait times by an average of 10 minutes per patient.
We implemented dashboards for hospitals and radiology centers, offering valuable business intelligence insights for informed decision-making.
