Tasks
- Enhancing AI models for improved efficiency.
- Transitioning systems to AWS for scalability.
- Consolidating data from various sources.
- Aligning releases with client design and usability needs
The main challenge was migrating to AWS managed services to enhance performance and scalability, consolidating data sources, and integrating client-specific design and usability needs.
Integration with R&D workflows; data privacy compliance.
Expert services reduce research time and costs by 15-20%, enhancing drug discovery success rates.
Integration with LIMS, compliance with regulatory standards and GMP.
Machine learning enhances HPLC capabilities, achieving a 20-25% increase in operational efficiency and reducing manual workload.
Integration with ERP/CRM systems; GDPR/HIPAA compliance.
ARIMA and LSTM models achieve 10-15% reduction in material waste.
Neural Network model for real-time sensor fusion to detect reactor issues, reducing failures by 40% and enhancing control capabilities.
Automated data collection and reporting, integrated systems, and enhanced decision-making with predictive analytics.
Developed an ML model for profiling transactions and clustering regular and irregular spending, improving user insights and app features.