Tag: AWS Partner Solutions Architects (SA)

Montoux’s next-generation decision science platform for insurers uniquely combines actuarial and data science in its software, providing a modern, flexible, and sophisticated alternative to legacy actuarial software. Learn how the AI-driven model replication module is specifically developed to support an insurer’s transition to cloud and reduces the time, cost, and effort required to migrate to a new platform.

To reap the benefits of cloud computing, organizations cannot simply take their existing applications and architectures in their legacy on-premises environment and move them as-is to the cloud. True cloud modernization with MongoDB Atlas on AWS enables you to move data and simultaneously apply the latest innovations in development methodologies, architectural patterns, and technologies to refresh your portfolio of existing applications.

By avoiding inspections, insurers lose the opportunity to adequately consider all factors during underwriting and take on more risk. TCS has built a virtual inspection solution on AWS that is customizable to various inspection use cases, such as home insurance inspections and claims, auto claims damage assessment and estimation, and mortgage inspection. This post provides an overview of the TCS virtual inspection solution, describes the high-level architecture, and explores the potential business benefits for insurers.

Security is the highest priority for AWS, which works closely with industry-leading partners such as CloudHealth by VMware to build security solutions for customers like CloudHealth Secure State (CHSS). Learn how you can set up CHSS projects, suppress rules and alerts, find misconfigurations through CHSS Explore, and set up remediation jobs all built on CloudHealth’s unified security monitoring approach for AWS.

A key challenge SaaS providers face is understanding the cost profile of their environment and the customers within it. Measuring the cost of each tenant in the system, understanding cost-effectiveness of product features, and accurately metering the margin in a SaaS solution are examples of abilities that are critical for SaaS success. Learn why breaking down the cost to different unit metrics, customers, features, segments, and business units is a requirement for any modern SaaS business.

Securing the Kubernetes environment without compromising on developer agility holds the key to success with cloud-native adoption. The Nirmata Kubernetes Platform is designed to address these challenges comprehensively. It’s an open and easy-to-adopt platform to deploy, operate, and optimize Kubernetes workloads on any infrastructure, enabling self-service, segregation of responsibilities, and security and governance controls.

As multi-tenant SaaS providers look to leverage machine learning services, they must consider how they’ll protect the data that flows in and out of these services from different tenants. Learn how tenant isolation of machine learning services can be achieved using AWS IAM, and how the integration between IAM, Amazon SageMaker, and many other AWS services provide developers with a rich set of mechanisms that can be applied to realize tenant isolation goals.

Element 84, in collaboration with AWS and Geoscience Australia, has released the Sentinel-2 Cloud-Optimized GeoTIFF (COG) dataset on AWS Open Data. Sentinel-2 is an important platform for Earth observation, and its imagery contributes to ongoing research in climate change, land use, and emergency management. By making the Sentinel-2 archive more cloud-native, we are making the data more user-friendly and (hopefully) making the lives of emergency managers, climate scientists, and policy makers that much easier.

Operationalizing machine learning models can be a challenge due to lack of established ML architecture and its integration with the existing landscape. DataRobot integrates with AWS and provides the flexibility for a model trained in DataRobot to be deployed on AWS services with centralized model governance, management, and monitoring. Learn how the DataRobot AutoML platform orchestrates the complete model development and training lifecycle.

Building an optimized mobile network requires careful planning to ensure proper coverage and capacity. This post discusses how CSPs can augment their existing network planning with additional data while leveraging analytics for cell site placement and network optimizations. Learn how Kinetica, a GPU-accelerated data platform, unites historical analytics and streaming analytics, location intelligence, graph analytics, and machine learning to tackle massive scale network data challenges.