Browse past weeks of engineering reads.
Industrial environments require generative AI capabilities to detect and resolve operational issues quickly, but deploying AI models reliably in offline or edge scenarios with limited connectivity is challenging.
How to implement secure, standardized data sharing across organizational boundaries while maintaining compliance with IDSA standards and the Dataspace Protocol.
Mapfre USA needed to detect insurance fraud in claims more effectively by moving beyond traditional rules-based and manual investigation approaches to leverage machine learning on large volumes of structured and unstructured data.
Storing and managing petabytes of distributed video surveillance data across thousands of locations while meeting growing retention requirements and enabling operational insights extraction.
S&P Global needed to implement a disaster recovery strategy for their Capital IQ platform that could achieve rapid failover to a secondary region while maintaining data consistency for mission-critical financial operations.
Avanse Financial Services needed to unify fragmented data engineering, analytics, and AI workflows across separate systems while maintaining governance and scalability for financial analytics.
Converting unstructured scanned PDF medical records into standardized, machine-readable FHIR R4-compliant healthcare data at scale.
Organizations need to extract structured, actionable insights from unstructured contract documents at scale to automate critical business processes.
Building Oracle database architectures that minimize recovery time and maximize availability while leveraging cloud infrastructure.
How to design systems that can recover from ransomware and destructive cyberattacks when backups, credentials, and infrastructure components have been compromised.
ALS GeoAnalytics needed to scale machine learning model training and inference for core logging analysis while managing computational costs effectively.
Oldcastle needed to overcome the limitations of traditional ERP reporting to enable real-time analytics and dashboards for their Infor ERP system.
Building a scalable multi-tenant configuration service that maintains strict tenant isolation while supporting real-time updates without cache staleness or downtime.
Organizations need a streamlined way to protect and recover entire AWS workloads across multiple layers (data, compute, infrastructure, networking, and configuration) in the event of a disaster.
BASF Digital Farming needed a scalable way to catalog, discover, and serve large volumes of spatiotemporal geospatial data (satellite imagery, crop data) for their xarvio crop optimization platform, and their existing infrastructure struggled with the scale and query patterns of this data.
Artera needed to develop and scale an AI-powered prostate cancer diagnostic test, requiring significant compute resources for model training/inference and a reliable pipeline to deliver timely, personalized treatment recommendations.
Organizations migrating to or operating in the cloud encounter hidden and unexpected costs due to suboptimal architectural decisions, resource misconfigurations, and lack of adherence to cloud best practices.