GOALS

• Accelerate drug discovery and development by leveraging AWS's high-performance computing and machine learning capabilities to analyze large genomic datasets
• Implement secure and compliant data storage and analytics solutions on AWS to meet strict regulatory requirements in the life sciences industry
• Build and deploy predictive models using AI and ML to identify potential drug targets and optimize clinical trial design.

Frustrations

• Finding it challenging to integrate various data sources and tools from different research partners and vendors within the AWS environment
• Experiencing difficulties in scaling their data analysis pipelines on AWS to handle the increasing volume and complexity of genomic data
• Ensuring the privacy and security of patient data while collaborating with external researchers and stakeholders on AWS cloud platform.

GOALS

• Modernize their core banking systems and applications by migrating them to AWS to improve agility, scalability, and reduce operational costs
• Enhance customer experience and drive innovation by leveraging AI and ML for personalized financial advice, fraud detection, and risk management
• Comply with stringent security and regulatory requirements in the financial services industry by implementing robust security measures on AWS.

Frustrations

• Encountering roadblocks in migrating legacy banking systems to AWS due to their complex architecture and dependencies on on-premises infrastructure
• Facing difficulties in attracting and retaining top engineering talent with expertise in both AWS cloud technologies and financial services regulations
• Balancing the need for rapid innovation in digital banking with the imperative to maintain the highest levels of security and compliance on the AWS platform.