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How TP ICAP transformed CRM data into real-time insights with Amazon Bedrock | Artificial Intelligence
This post shows how TP ICAP used Amazon Bedrock Knowledge Bases and Amazon Bedrock Evaluations to build ClientIQ, an enterprise-grade solution with enhanced security features for extracting CRM insights using AI, delivering immediate business value.
Principal Financial Group accelerates build, test, and deployment of Amazon Lex V2 bots through automation | Artificial Intelligence
In the post Principal Financial Group increases Voice Virtual Assistant performance using Genesys, Amazon Lex, and Amazon QuickSight, we discussed the overall Principal Virtual Assistant solution using Genesys Cloud, Amazon Lex V2, multiple AWS services, and a custom reporting and analytics solution using Amazon QuickSight.
Splash Music transforms music generation using AWS Trainium and Amazon SageMaker HyperPod | Artificial Intelligence
In this post, we show how Splash Music is setting a new standard for AI-powered music creation by using its advanced HummingLM model with AWS Trainium on Amazon SageMaker HyperPod. As a selected startup in the 2024 AWS Generative AI Accelerator, Splash Music collaborated closely with AWS Startups and the AWS Generative AI Innovation Center (GenAIIC) to fast-track innovation and accelerate their music generation FM development lifecycle.
Stream mainframe data to AWS in near real time with Precisely and Amazon MSK | AWS Big Data Blog
In this post, we introduce an alternative architecture to synchronize mainframe data to the cloud using Amazon Managed Streaming for Apache Kafka (Amazon MSK) for greater flexibility and scalability. This event-driven approach provides additional possibilities for mainframe data integration and modernization strategies.
Optimizing document AI and structured outputs by fine-tuning Amazon Nova Models and on-demand inference | Artificial Intelligence
This post provides a comprehensive hands-on guide to fine-tune Amazon Nova Lite for document processing tasks, with a focus on tax form data extraction. Using our open-source GitHub repository code sample, we demonstrate the complete workflow from data preparation to model deployment.
Voice AI-powered drive-thru ordering with Amazon Nova Sonic and dynamic menu displays | Artificial Intelligence
In this post, we'll demonstrate how to implement a Quick Service Restaurants (QSRs) drive-thru solution using Amazon Nova Sonic and AWS services. We'll walk through building an intelligent system that combines voice AI with interactive menu displays, providing technical insights and implementation guidance to help restaurants modernize their drive-thru operations.
Performance optimization strategies for MySQL on Amazon RDS | AWS Database Blog
In this post, we share infrastructure-level optimizations, RDS-specific performance features, and database design patterns to help improve MySQL performance on Amazon RDS. We focus on practical configurations and monitoring techniques that complement existing parameter tuning documentation, helping you make informed decisions for your specific workload requirements.
Iterative fine-tuning on Amazon Bedrock for strategic model improvement | Artificial Intelligence
Organizations often face challenges when implementing single-shot fine-tuning approaches for their generative AI models. The single-shot fine-tuning method involves selecting training data, configuring hyperparameters, and hoping the results meet expectations without the ability to make incremental adjustments. Single-shot fine-tuning frequently leads to suboptimal results and requires starting the entire process from scratch when improvements are […]
Configure and verify a distributed training cluster with AWS Deep Learning Containers on Amazon EKS | Artificial Intelligence
Misconfiguration issues in distributed training with Amazon EKS can be prevented following a systematic approach to launch required components and verify their proper configuration. This post walks through the steps to set up and verify an EKS cluster for training large models using DLCs.
Best practices for upgrading from Amazon Redshift DC2 to RA3 and Amazon Redshift Serverless | AWS Big Data Blog
As analytical demands grow, many customers are upgrading from DC2 to RA3 or Amazon Redshift Serverless, which offer independent compute and storage scaling, along with advanced capabilities such as data sharing, zero-ETL integration, and built-in artificial intelligence and machine learning (AI/ML) support with Amazon Redshift ML. This post provides a practical guide to plan your target architecture and migration strategy, covering upgrade options, key considerations, and best practices to facilitate a successful and seamless transition.
Building smarter AI agents: AgentCore long-term memory deep dive | Artificial Intelligence
In this post, we explore how Amazon Bedrock AgentCore Memory transforms raw conversational data into persistent, actionable knowledge through sophisticated extraction, consolidation, and retrieval mechanisms that mirror human cognitive processes. The system tackles the complex challenge of building AI agents that don't just store conversations but extract meaningful insights, merge related information across time, and maintain coherent memory stores that enable truly context-aware interactions.
Transforming enterprise operations: Four high-impact use cases with Amazon Nova | Artificial Intelligence
In this post, we share four high-impact, widely adopted use cases built with Nova in Amazon Bedrock, supported by real-world customers deployments, offerings available from AWS partners, and experiences. These examples are ideal for organizations researching their own AI adoption strategies and use cases across industries.
How Amazon Bedrock Custom Model Import streamlined LLM deployment for Salesforce | Artificial Intelligence
This post shows how Salesforce integrated Amazon Bedrock Custom Model Import into their machine learning operations (MLOps) workflow, reused existing endpoints without application changes, and benchmarked scalability. We share key metrics on operational efficiency and cost optimization gains, and offer practical insights for simplifying your deployment strategy.
Amazon Aurora MySQL zero-ETL integration with Amazon SageMaker Lakehouse | AWS Database Blog
In this post, we explore how zero-ETL integration works, the key benefits it delivers for data-driven teams, and how it aligns with the broader zero-ETL strategy in AWS services. You'll learn how this integration can enhance your data workflows, whether you're building predictive models, entering interactive SQL queries, or visualizing business trends. By eliminating traditional extract, transform, and load (ETL) processes, this solution enables real-time intelligence securely and at scale to help you make faster, data-driven decisions.
Build a device management agent with Amazon Bedrock AgentCore | Artificial Intelligence
In this post, we explore how to build a conversational device management system using Amazon Bedrock AgentCore. With this solution, users can manage their IoT devices through natural language, using a UI for tasks like checking device status, configuring WiFi networks, and monitoring user activity.
Transform your Oracle Database journey with Accenture and AWS | AWS Database Blog
In this post, we explore how enterprises can transform their Oracle Database environments by combining Accenture’s proven migration expertise with Oracle Database@AWS’s innovative capabilities to achieve faster modernization, enhanced performance, and seamless integration with AWS services
Visualize data lineage using Amazon SageMaker Catalog for Amazon EMR, AWS Glue, and Amazon Redshift | AWS Big Data Blog
Amazon SageMaker offers a comprehensive hub that integrates data, analytics, and AI capabilities, providing a unified experience for users to access and work with their data. Through Amazon SageMaker Unified Studio, a single and unified environment, you can use a wide range of tools and features to support your data and AI development needs, including […]
Connect Amazon Quick Suite to enterprise apps and agents with MCP | Artificial Intelligence
In this post, we explore how Amazon Quick Suite's Model Context Protocol (MCP) client enables secure, standardized connections to enterprise applications and AI agents, eliminating the need for complex custom integrations. You'll discover how to set up MCP Actions integrations with popular enterprise tools like Atlassian Jira and Confluence, AWS Knowledge MCP Server, and Amazon Bedrock AgentCore Gateway to create a collaborative environment where people and AI agents can seamlessly work together across your organization's data and applications.
Kitsa transforms clinical trial site selection with Amazon Quick Automate | Artificial Intelligence
In this post, we'll show how Kitsa, a health-tech company specializing in AI-driven clinical trial recruitment and site selection, used Amazon Quick Automate to transform their clinical trial site selection solution. Amazon Quick Automate, a capability of Amazon Quick Suite, enables enterprises to build, deploy and maintain resilient workflow automations at scale.
Transforming the physical world with AI: the next frontier in intelligent automation | Artificial Intelligence
In this post, we explore how Physical AI represents the next frontier in intelligent automation, where artificial intelligence transcends digital boundaries to perceive, understand, and manipulate the tangible world around us.
Medical reports analysis dashboard using Amazon Bedrock, LangChain, and Streamlit | Artificial Intelligence
In this post, we demonstrate the development of a conceptual Medical Reports Analysis Dashboard that combines Amazon Bedrock AI capabilities, LangChain's document processing, and Streamlit's interactive visualization features. The solution transforms complex medical data into accessible insights through a context-aware chat system powered by large language models available through Amazon Bedrock and dynamic visualizations of health parameters.
Announcing vector search for Amazon ElastiCache | AWS Database Blog
Vector search for Amazon ElastiCache is now generally available. You can now use ElastiCache to index, search, and update billions of high-dimensional vector embeddings from popular providers like Amazon Bedrock, Amazon SageMaker, Anthropic, and OpenAI—with latencies as low as microseconds and up to 99% recall.
Building a real-time ICU patient analytics pipeline with AWS Lambda event source mapping | AWS Big Data Blog
In this post, we demonstrate how to build a serverless architecture that processes real-time ICU patient monitoring data using Lambda event source mapping for immediate alert generation and data aggregation, followed by persistent storage in Amazon S3 with an Iceberg catalog for comprehensive healthcare analytics.
Use Amazon SageMaker HyperPod and Anyscale for next-generation distributed computing | Artificial Intelligence
In this post, we demonstrate how to integrate Amazon SageMaker HyperPod with Anyscale platform to address critical infrastructure challenges in building and deploying large-scale AI models. The combined solution provides robust infrastructure for distributed AI workloads with high-performance hardware, continuous monitoring, and seamless integration with Ray, the leading AI compute engine, enabling organizations to reduce time-to-market and lower total cost of ownership.
Advanced observability and troubleshooting with Amazon RDS event monitoring pipelines | AWS Database Blog
AWS provides a wide range of monitoring solutions for your Amazon RDS and Amazon Aurora instances, such as Amazon CloudWatch, Amazon CloudWatch Database Insights, and AWS CloudTrail. Amazon RDS event monitoring pipelines make troubleshooting operational events like reboots, errors, and failovers more efficient. In this post, we present a solution to get a head start on troubleshooting by sending an email after a reboot or failover with the last 10 minutes of important CloudWatch metrics, top queries, and related API calls performed on the instance.
Customizing text content moderation with Amazon Nova | Artificial Intelligence
In this post, we introduce Amazon Nova customization for text content moderation through Amazon SageMaker AI, enabling organizations to fine-tune models for their specific moderation needs. The evaluation across three benchmarks shows that customized Nova models achieve an average improvement of 7.3% in F1 scores compared to the baseline Nova Lite, with individual improvements ranging from 4.2% to 9.2% across different content moderation tasks.
Implement a secure MLOps platform based on Terraform and GitHub | Artificial Intelligence
Machine learning operations (MLOps) is the combination of people, processes, and technology to productionize ML use cases efficiently. To achieve this, enterprise customers must develop MLOps platforms to support reproducibility, robustness, and end-to-end observability of the ML use case’s lifecycle. Those platforms are based on a multi-account setup by adopting strict security constraints, development best […]
Building a 10-billion wallet crypto-intelligence platform: Elliptic’s journey with Amazon DynamoDB | AWS Database Blog
In this post, we explore how Elliptic uses Amazon DynamoDB to build a crypto-intelligence platform that scales to over 10 billion wallets globally and supports real-time risk detection across the fast-evolving digital asset ecosystem. We discuss the data model design, indexing strategies, and operational setup that Elliptic uses to power real-time risk analysis and complex investigations at scale.
Monitor Amazon Timestream for InfluxDB performance using the Timestream for InfluxDB Metrics dashboard | AWS Database Blog
The Timestream for InfluxDB Metrics dashboard adds the ability to perform trend analysis, create actionable insights, set up alerts, and automate reporting. You can configure the Timestream for InfluxDB Metrics dashboard to suit your business needs and build a robust and optimized time series workflow. In this post we walk you through how to deploy the Timestream for InfluxDB Metrics dashboard to start monitoring the performance of your fleet of Timestream for InfluxDB databases.
Implement automated monitoring for Amazon Bedrock batch inference | Artificial Intelligence
In this post, we demonstrated how a financial services company can use an FM to process large volumes of customer records and get specific data-driven product recommendations. We also showed how to implement an automated monitoring solution for Amazon Bedrock batch inference jobs. By using EventBridge, Lambda, and DynamoDB, you can gain real-time visibility into batch processing operations, so you can efficiently generate personalized product recommendations based on customer credit data.
Best practices for migrating from Apache Airflow 2.x to Apache Airflow 3.x on Amazon MWAA | AWS Big Data Blog
Apache Airflow 3.x on Amazon MWAA introduces architectural improvements such as API-based task execution that provides enhanced security and isolation. This migration presents an opportunity to embrace next-generation workflow orchestration capabilities while providing business continuity. This post provides best practices and a streamlined approach to successfully navigate this critical migration, providing minimal disruption to your mission-critical data pipelines while maximizing the enhanced capabilities of Airflow 3.
Bridging data silos: cross-bounded context querying with Vanguard’s Operational Read-only Data Store (ORDS) using Amazon Redshift | AWS Big Data Blog
At Vanguard, we faced significant challenges with our legacy mainframe system that limited our ability to deliver modern, personalized customer experiences. Our centralized database architecture created performance bottlenecks and made it difficult to scale services independently for our millions of personal and institutional investors. In this post, we show you how we modernized our data architecture using Amazon Redshift as our Operational Read-only Data Store (ORDS).
Seamlessly Integrate Data on Google BigQuery and ClickHouse Cloud with AWS Glue | AWS Big Data Blog
Migrating from Google Cloud’s BigQuery to ClickHouse Cloud on AWS allows businesses to leverage the speed and efficiency of ClickHouse for real-time analytics while benefiting from AWS’s scalable and secure environment. This article provides a comprehensive guide to executing a direct data migration using AWS Glue ETL, highlighting the advantages and best practices for a […]