Category: Serverless

TextRay is an information extraction solution that automatically extracts data from scanned documents using deep learning models. It leverages AWS services to provide a scalable and cost-effective way to process documents while reducing errors and turnaround time. An AWS CloudFormation template simplifies deployment, while a pre-trained base model demonstrates TextRay’s precision in extracting tabular and form data into structured CSV outputs.

The world of video entertainment is more competitive than ever. The video entertainment landscape is crowded, so content providers must deeply understand viewer behavior to stand out. Synamedia Clarissa, built on AWS, delivers data-driven insights to help businesses boost viewer satisfaction. Clarissa analyzes video consumption and user experiences, providing content and app insights like which videos resonate best and how users discover content.

Pinecone has developed a novel serverless vector database architecture optimized for AI workloads like retrieval-augmented generation. Built on AWS, it decouples storage and compute and enables efficient intermittent querying of large datasets. This provides elasticity, fresher data, and major cost savings over traditional architectures. Pinecone serverless removes bottlenecks to building more knowledgeable AI applications economically at scale on AWS.

KewSustain is an AI platform by KewMann built on AWS that addresses gaps in sustainability compliance. It efficiently gathers ESG data from multiple sources, analyzes it, and generates sustainability reports adhering to major frameworks. Key features include automated data collection, collaboration tools, recommendations based on various risk factors, real-time insights via dashboards, and a virtual assistant providing guidance on reporting requirements.

Leveraging AWS Lambda response streaming functionality enables progressive data delivery from large datasets, enhancing web application performance. This post compares a traditional API implementation to a Lambda streaming API, demonstrating reduced time-to-first-byte latency and quicker, more dynamic client-side rendering. By incrementally sending data, response streaming eliminates lag from waiting on entire dataset transfers, vastly improving user experience for data-intensive applications.

Noventiq developed uDMS, a smart document management system hosted on AWS serverless architecture that removes the need to manage servers while ensuring scalability, cost-efficiency, and global accessibility. uDMS offers easy document tracking, metadata templating, workflow notifications, version control, and integrates well with other systems. It demonstrates how a serverless architecture can enable rapid deployment and modernization of legacy document management systems.

Verana Health leverages an exclusive real-world data network and AI-enhanced data engine to transform healthcare data into curated, disease-specific data modules called Qdata. This powers Verana’s analytics solutions for real-world evidence generation, clinical trials, quality reporting, and registry data management to enhance patient care and quality of life. Through AWS Data Exchange and Amazon Redshift, Verana offers life sciences customers easy, convenient access to high-quality clinical real-world data for research.

Organizations are rapidly adopting containerized environments using AWS Fargate for developer efficiency. Sysdig uses advanced instrumentation to provide real-time visibility into AWS Fargate containers to detect threats. With policies and automatic response, Sysdig Secure enables AWS Fargate workload protection without requiring code changes. As an AWS Specialization Partner, Sysdig helps secure cloud-native applications on AWS.

CyberCX built an AWS serverless data lake and data masking solution to enable using production data securely in non-production environments. The modular, AWS-native solution combines AWS services to mask sensitive data in near real-time while retaining data utility. This allows thorough testing and confidence before deployment to production, improving data security and accelerating time to market.

Many startups want to use machine learning but struggle with developing scalable MLOps pipelines. Automat-IT’s MLOps Accelerator helps startups fast-track their machine learning journey and provides an end-to-end automated solution for the ML lifecycle, from data preparation to deployment, leveraging AWS services. With customizable pipelines and dedicated ML experts, Automat-IT empowers various roles to develop, operationalize, and monitor models efficiently.