AWS Partner Network (APN) Blog

Category: Amazon Machine Learning

Metal Toad launches Securitoad on AWS Marketplace – AI powered cyber threat prevention

In this exclusive interview for our blog, we sat down with Joaquin Lippincott, the CEO of Metal Toad, to delve into the innovative Securitoad Machine Learning Security SaaS solution. Joaquin generously shared his expertise on how they strategically built their latest offering on the AWS Marketplace. His insights offer invaluable lessons for software providers aiming to embrace this modern delivery mode.

Building a data foundation for AI using Snowflake and AWS

Snowflake By Daniel Wirjo, Solutions Architect – AWS By Benny Chun, Solutions Architect – AWS By Bosco Albuquerque, Sr. Partner Solutions Architect – AWS By Hans Siebrand, Cloud Data Architect – Snowflake By Matt Marzillo, Sr. Partner Engineer – Snowflake With recent advancements, building a data platform to provide a data foundation for generative AI […]

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HCL Workload Automation expands AWS integration with AWS Step Functions

HCLSoftware’s automation product, HCL Workload Automation (HWA), now integrates with AWS Step Functions. This integration offers a comprehensive automation solution, streamlining complex workflows across cloud and on-premises environments. It enables organizations to automate more use cases with increased efficiency, scalability, and reliability, utilizing the robust AWS ecosystem of services. This strategic partnership empowers customers to transform their IT landscape through centralized, cloud-native automation.

How AWS Partners are Driving Innovation and Efficiency with Amazon Bedrock and Amazon Q

In April, Amazon Web Services (AWS) unveiled a suite of groundbreaking features for Amazon Bedrock and Amazon Q, ushering in a new era of generative AI capabilities. Learn how AWS Partners are leveraging the latest Amazon Bedrock and Amazon Q features to transform how they build, scale, and deploy intelligent applications—unlocking unprecedented opportunities for innovation and efficiency.

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How Arcanum AI Migrated Models from OpenAI to AWS Using Amazon Bedrock and Amazon SageMaker JumpStart

Arcanum AI migrated its generative AI workloads from OpenAI to AWS using a two-phase model evaluation process. Open-source LLMs were tested out-of-the-box and with customized prompts, scored by experts, and evaluated against existing use cases. Amazon Bedrock provided a private network and access control for handling sensitive client data. AWS’s AI services enabled Arcanum to deploy top-performing LLMs securely in clients’ VPCs, outperforming OpenAI models while meeting security needs.

Building a Scalable DICOM Ingestion Pipeline for AWS HealthImaging with CitiusTech

AWS HealthImaging is a new HIPAA-eligible service for storing, analyzing, and sharing medical imaging data securely in the cloud. CitiusTech developed a solution leveraging AWS services like HealthImaging to automate ingesting DICOM data. It scans for malware, validates DICOM files, copies clean images to HealthImaging for storage, and notifies users. Healthcare providers can easily migrate imaging workloads to realize improved accessibility and cost-efficiency.

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How Shellkode Uses Amazon Bedrock to Convert Natural Language Queries to NoSQL Statements

Large language models like Amazon Bedrock can generate MongoDB queries from natural language questions, transforming how users access NoSQL databases. By leveraging AI and language models, this solution allows business users to query MongoDB data through conversational English instead of code. It connects to MongoDB with PyMongo, generates queries with LangChain and Bedrock, retrieves and formats results into natural language answers.

Develop and Deploy Machine Learning Models with Eviden’s Comprehensive Approach to MLOps Assessment

MLOps applies DevOps principles to machine learning, enabling organizations to efficiently develop, deploy, and manage models at scale. Eviden’s 10-step MLOps assessment examines existing models, establishes governance, creates self-service access, scales data analysis, registers models, enables feature re-use, provides data access, tests models at scale, deploys models, and enables API access. This end-to-end approach streamlines model creation and deployment while ensuring governance and consistency.

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Building a Data Foundation for Healthcare Transformation with Redox, Cloudwick, ClearDATA, and AWS

Healthcare organizations have vast amounts of valuable but siloed data. A new solution from AWS Partners Redox, Cloudwick, and ClearDATA helps healthcare customers use AWS HealthLake to extract value from their data. Redox integrates and translates data into AWS, while ClearDATA provides 24/7 security and compliance, and Cloudwick Amorphic enables teams to quickly build analytics and workflows to improve care.

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Transforming Customer Service with Rapyder’s Generative AI-Powered Call Agent Analyzer

Rapyder’s Call Agent Analyzer uses generative AI on AWS to revolutionize call center operations. It efficiently processes multilingual audio, summarizes calls, analyzes script adherence, and structures insights into actionable data. This solution helps businesses enhance customer satisfaction through data-driven call agent performance evaluation and training. As an AWS Partner, Rapyder provides cutting-edge cloud solutions that are reshaping industries like customer service.