AWS Partner Network (APN) Blog
Category: Amazon Bedrock
A qualitative approach to Evaluating Large Language Models for Responsible Gen AI on AWS
Evaluating Large Language Models (LLMs) for the responsible deployment of Generative AI applications is a critical aspect of this journey. Learn how Caylent’s solution enables customers to build a human-in-the-loop LLM evaluation and benchmarking workflow.
Hexaware’s Gen AI Review Analytics Solution for Retail Enterprises
By: Hamdy Eed, Sr. Partner Solution Architect – AWS By: A. Soundarapandian, Data Science Practice Head – Hexaware By: Teena Jain, GenAI Solution Lead – Hexaware By: Zeba Shaikh, Technical Solution Architect – Hexaware By: Piyush Patra, Partner Solution Architect – AWS Introduction: In this blog post, we will focus on equipping our readers with […]
Neurons Lab – Transforming Cybersecurity Audits with Generative AI on AWS
In this blog, you’ll learn how Neurons Lab, an AWS Advanced Tier Services Partner, collaborated with Peak Defence to automate compliance processes using Amazon Bedrock with Anthropic Claude 3 model and Amazon Sagemaker. The generative AI solution streamlines cybersecurity audits and RFP responses, reducing time and resources required. It covers architectural considerations, operationalization with AWS services, LLM evaluation, and continuous improvement.
Wipro applying Data, AI/ML and Generative AI to the Telecom Industry
By Vanitha Jayasuriya, Full Stride Cloud Solution Lead, Germany – Wipro By Yedu Kuruvath, Alliances and Partner Development Lead, AI Practice – Wipro By Shaban Saddique, AWS Business Group Director, Europe – Wipro By Benson Philip, Sr Partner Development Manager, EMEA – AWS By Bindhu Chinnadurai, Sr Partner Solutions Architect, EMEA – AWS Wipro Introduction […]
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 […]
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.
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.
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.
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.