Build a gen AI–powered financial assistant with Amazon Bedrock multi-agent collaboration

The Amazon Bedrock multi-agent collaboration feature gives developers the flexibility to create and coordinate multiple AI agents, each specialized for specific tasks, to work together efficiently on complex business processes. This enables seamless handling of sophisticated workflows through agent cooperation. This post aims to demonstrate the application of multiple specialized agents within the Amazon Bedrock … Read more

WordFinder app: Harnessing generative AI on AWS for aphasia communication

In this post, we showcase how Dr. Kori Ramajoo, Dr. Sonia Brownsett, Prof. David Copland, from QARC, and Scott Harding, a person living with aphasia, used AWS services to develop WordFinder, a mobile, cloud-based solution that helps individuals with aphasia increase their independence through the use of AWS generative AI technology. In the spirit of … Read more

Get faster and actionable AWS Trusted Advisor insights to make data-driven decisions using Amazon Q Business

Our customers’ key strategic objectives are cost savings and building secure and resilient infrastructure. At AWS, we’re dedicated to helping you meet these critical goals with our unparalleled expertise and industry-leading tools. One of the most valuable resources we offer is the AWS Trusted Advisor detailed report, which provides deep insights into cost optimization, security … Read more

Best practices for Meta Llama 3.2 multimodal fine-tuning on Amazon Bedrock

Multimodal fine-tuning represents a powerful approach for customizing foundation models (FMs) to excel at specific tasks that involve both visual and textual information. Although base multimodal models offer impressive general capabilities, they often fall short when faced with specialized visual tasks, domain-specific content, or particular output formatting requirements. Fine-tuning addresses these limitations by adapting models … Read more

Extend large language models powered by Amazon SageMaker AI using Model Context Protocol

Organizations implementing agents and agent-based systems often experience challenges such as implementing multiple tools, function calling, and orchestrating the workflows of the tool calling. An agent uses a function call to invoke an external tool (like an API or database) to perform specific actions or retrieve information it doesn’t possess internally. These tools are integrated … Read more

Automate document translation and standardization with Amazon Bedrock and Amazon Translate

Multinational organizations face the complex challenge of effectively managing a workforce and operations across different countries, cultures, and languages. Maintaining consistency and alignment across these global operations can be difficult, especially when it comes to updating and sharing business documents and processes. Delays or miscommunications can lead to productivity losses, operational inefficiencies, or potential business … Read more

Autonomous mortgage processing using Amazon Bedrock Data Automation and Amazon Bedrock Agents

Mortgage processing is a complex, document-heavy workflow that demands accuracy, efficiency, and compliance. Traditional mortgage operations rely on manual review, rule-based automation, and disparate systems, often leading to delays, errors, and a poor customer experience. Recent industry surveys indicate that only about half of borrowers express satisfaction with the mortgage process, with traditional banks trailing … Read more

Amazon Bedrock Model Distillation: Boost function calling accuracy while reducing cost and latency

Amazon Bedrock Model Distillation is generally available, and it addresses the fundamental challenge many organizations face when deploying generative AI: how to maintain high performance while reducing costs and latency. This technique transfers knowledge from larger, more capable foundation models (FMs) that act as teachers to smaller, more efficient models (students), creating specialized models that … Read more

Build public-facing generative AI applications using Amazon Q Business for anonymous users

Amazon Q Business is a generative AI-powered assistant that answers question, provides summaries, generates content, and securely completes tasks based on enterprise data and information. It connects to company data sources, applications, and internal systems to provide relevant, contextual answers while maintaining organizational security and compliance standards. Today, we’re excited to announce that Amazon Q … Read more

FloQast builds an AI-powered accounting transformation solution with Anthropic’s Claude 3 on Amazon Bedrock

With the advent of generative AI solutions, a paradigm shift is underway across industries, driven by organizations embracing foundation models (FMs) to unlock unprecedented opportunities. Amazon Bedrock has emerged as the preferred choice for numerous customers seeking to innovate and launch generative AI applications, leading to an exponential surge in demand for model inference capabilities. … Read more

Insights in implementing production-ready solutions with generative AI

As generative AI revolutionizes industries, organizations are eager to harness its potential. However, the journey from production-ready solutions to full-scale implementation can present distinct operational and technical considerations. This post explores key insights and lessons learned from AWS customers in Europe, Middle East, and Africa (EMEA) who have successfully navigated this transition, providing a roadmap … Read more

Responsible AI in action: How Data Reply red teaming supports generative AI safety on AWS

Generative AI is rapidly reshaping industries worldwide, empowering businesses to deliver exceptional customer experiences, streamline processes, and push innovation at an unprecedented scale. However, amidst the excitement, critical questions around the responsible use and implementation of such powerful technology have started to emerge. Although responsible AI has been a key focus for the industry over … Read more

InterVision accelerates AI development using AWS LLM League and Amazon SageMaker AI

Cities and local governments are continuously seeking ways to enhance their non-emergency services, recognizing that intelligent, scalable contact center solutions play a crucial role in improving citizen experiences. InterVision Systems, LLC (InterVision), an AWS Premier Tier Services Partner and Amazon Connect Service Delivery Partner, has been at the forefront of this transformation, with their contact … Read more

Improve Amazon Nova migration performance with data-aware prompt optimization

In the era of generative AI, new large language models (LLMs) are continually emerging, each with unique capabilities, architectures, and optimizations. Among these, Amazon Nova foundation models (FMs) deliver frontier intelligence and industry-leading cost-performance, available exclusively on Amazon Bedrock. Since its launch in 2024, generative AI practitioners, including the teams in Amazon, have started transitioning … Read more

Customize Amazon Nova models to improve tool usage

Modern large language models (LLMs) excel in language processing but are limited by their static training data. However, as industries require more adaptive, decision-making AI, integrating tools and external APIs has become essential. This has led to the evolution and rapid rise of agentic workflows, where AI systems autonomously plan, execute, and refine tasks. Accurate … Read more

Evaluate Amazon Bedrock Agents with Ragas and LLM-as-a-judge

AI agents are quickly becoming an integral part of customer workflows across industries by automating complex tasks, enhancing decision-making, and streamlining operations. However, the adoption of AI agents in production systems requires scalable evaluation pipelines. Robust agent evaluation enables you to gauge how well an agent is performing certain actions and gain key insights into … Read more

Enterprise-grade natural language to SQL generation using LLMs: Balancing accuracy, latency, and scale

This blog post is co-written with Renuka Kumar and Thomas Matthew from Cisco. Enterprise data by its very nature spans diverse data domains, such as security, finance, product, and HR. Data across these domains is often maintained across disparate data environments (such as Amazon Aurora, Oracle, and Teradata), with each managing hundreds or perhaps thousands … Read more

AWS Field Experience reduced cost and delivered low latency and high performance with Amazon Nova Lite foundation model

AWS Field Experience (AFX) empowers Amazon Web Services (AWS) sales teams with generative AI solutions built on Amazon Bedrock, improving how AWS sellers and customers interact. The AFX team uses AI to automate tasks and provide intelligent insights and recommendations, streamlining workflows for both customer-facing roles and internal support functions. Their approach emphasizes operational efficiency … Read more

Combine keyword and semantic search for text and images using Amazon Bedrock and Amazon OpenSearch Service

Customers today expect to find products quickly and efficiently through intuitive search functionality. A seamless search journey not only enhances the overall user experience, but also directly impacts key business metrics such as conversion rates, average order value, and customer loyalty. According to a McKinsey study, 78% of consumers are more likely to make repeat … Read more

Build an AI-powered document processing platform with open source NER model and LLM on Amazon SageMaker

Archival data in research institutions and national laboratories represents a vast repository of historical knowledge, yet much of it remains inaccessible due to factors like limited metadata and inconsistent labeling. Traditional keyword-based search mechanisms are often insufficient for locating relevant documents efficiently, requiring extensive manual review to extract meaningful insights. To address these challenges, a … Read more

Protect sensitive data in RAG applications with Amazon Bedrock

Retrieval Augmented Generation (RAG) applications have become increasingly popular due to their ability to enhance generative AI tasks with contextually relevant information. Implementing RAG-based applications requires careful attention to security, particularly when handling sensitive data. The protection of personally identifiable information (PII), protected health information (PHI), and confidential business data is crucial because this information … Read more

Supercharge your LLM performance with Amazon SageMaker Large Model Inference container v15

Today, we’re excited to announce the launch of Amazon SageMaker Large Model Inference (LMI) container v15, powered by vLLM 0.8.4 with support for the vLLM V1 engine. This version now supports the latest open-source models, such as Meta’s Llama 4 models Scout and Maverick, Google’s Gemma 3, Alibaba’s Qwen, Mistral AI, DeepSeek-R, and many more. … Read more

Accuracy evaluation framework for Amazon Q Business – Part 2

In the first post of this series, we introduced a comprehensive evaluation framework for Amazon Q Business, a fully managed Retrieval Augmented Generation (RAG) solution that uses your company’s proprietary data without the complexity of managing large language models (LLMs). The first post focused on selecting appropriate use cases, preparing data, and implementing metrics to … Read more

Use Amazon Bedrock Intelligent Prompt Routing for cost and latency benefits

In December, we announced the preview availability for Amazon Bedrock Intelligent Prompt Routing, which provides a single serverless endpoint to efficiently route requests between different foundation models within the same model family. To do this, Amazon Bedrock Intelligent Prompt Routing dynamically predicts the response quality of each model for a request and routes the request to … Read more

How Infosys improved accessibility for Event Knowledge using Amazon Nova Pro, Amazon Bedrock and Amazon Elemental Media Services

This post is co-written with Saibal Samaddar, Tanushree Halder, and Lokesh Joshi from Infosys Consulting. Critical insights and expertise are concentrated among thought leaders and experts across the globe. Language barriers often hinder the distribution and comprehension of this knowledge during crucial encounters. Workshops, conferences, and training sessions serve as platforms for collaboration and knowledge … Read more

Amazon Bedrock Prompt Optimization Drives LLM Applications Innovation for Yuewen Group

Yuewen Group is a global leader in online literature and IP operations. Through its overseas platform WebNovel, it has attracted about 260 million users in over 200 countries and regions, promoting Chinese web literature globally. The company also adapts quality web novels into films, animations for international markets, expanding the global influence of Chinese culture. … Read more

Build a location-aware agent using Amazon Bedrock Agents and Foursquare APIs

This post is co-written with Vikram Gundeti and Nate Folkert from Foursquare. Personalization is key to creating memorable experiences. Whether it’s recommending the perfect movie or suggesting a new restaurant, tailoring suggestions to individual preferences can make all the difference. But when it comes to food and activities, there’s more to consider than just personal … Read more

Build an automated generative AI solution evaluation pipeline with Amazon Nova

Large language models (LLMs) have become integral to numerous applications across industries, ranging from enhanced customer interactions to automated business processes. Deploying these models in real-world scenarios presents significant challenges, particularly in ensuring accuracy, fairness, relevance, and mitigating hallucinations. Thorough evaluation of the performance and outputs of these models is therefore critical to maintaining trust … Read more

Build a FinOps agent using Amazon Bedrock with multi-agent capability and Amazon Nova as the foundation model

AI agents are revolutionizing how businesses enhance their operational capabilities and enterprise applications. By enabling natural language interactions, these agents provide customers with a streamlined, personalized experience. Amazon Bedrock Agents uses the capabilities of foundation models (FMs), combining them with APIs and data to process user requests, gather information, and execute specific tasks effectively. The … Read more

Stream ingest data from Kafka to Amazon Bedrock Knowledge Bases using custom connectors

Retrieval Augmented Generation (RAG) enhances AI responses by combining the generative AI model’s capabilities with information from external data sources, rather than relying solely on the model’s built-in knowledge. In this post, we showcase the custom data connector capability in Amazon Bedrock Knowledge Bases that makes it straightforward to build RAG workflows with custom input … Read more