Generative AI applications seem simple—invoke a foundation model (FM) with the right context to generate a response. In reality, it’s a much more complex system involving workflows that invoke FMs, tools, and APIs and that use domain-specific data to ground responses with patterns such as Retrieval Augmented Generation (RAG) and workflows involving agents. Safety controls … Read more
When ingesting data into Amazon OpenSearch, customers often need to augment data before putting it into their indexes. For instance, you might be ingesting log files with an IP address and want to get a geographic location for the IP address, or you might be ingesting customer comments and want to identify the language they … Read more
In the landscape of generative AI, organizations are increasingly adopting a structured approach to deploy their AI applications, mirroring traditional software development practices. This approach typically involves separate development and production environments, each with its own AWS account, to create logical separation, enhance security, and streamline workflows. Amazon Bedrock is a fully managed service that … Read more
Emerging transformer-based vision models for geospatial data—also called geospatial foundation models (GeoFMs)—offer a new and powerful technology for mapping the earth’s surface at a continental scale, providing stakeholders with the tooling to detect and monitor surface-level ecosystem conditions such as forest degradation, natural disaster impact, crop yield, and many others. GeoFMs represent an emerging research … Read more
Agentic Retrieval Augmented Generation (RAG) applications represent an advanced approach in AI that integrates foundation models (FMs) with external knowledge retrieval and autonomous agent capabilities. These systems dynamically access and process information, break down complex tasks, use external tools, apply reasoning, and adapt to various contexts. They go beyond simple question answering by performing multi-step … Read more
AI image generation has emerged as one of the most transformative technologies in recent years, revolutionizing how you create and interact with visual content. Amazon Nova Canvas is a generative model in the suite of Amazon Nova creative models that enables you to generate realistic and creative images from plain text descriptions. This post serves … Read more
As AI image generation becomes increasingly central to modern business workflows, organizations are seeking practical ways to implement this technology for specific industry challenges. Although the potential of AI image generation is vast, many businesses struggle to effectively apply it to their unique use cases. In this post, we explore how Amazon Nova Canvas can … Read more
In the financial services industry, analysts need to switch between structured data (such as time-series pricing information), unstructured text (such as SEC filings and analyst reports), and audio/visual content (earnings calls and presentations). Each format requires different analytical approaches and specialized tools, creating workflow inefficiencies. Add on top of this the intense time pressure resulting … Read more
It takes biopharma companies over 10 years, at a cost of over $2 billion and with a failure rate of over 90%, to deliver a new drug to patients. The Market to Molecule (M2M) value stream process, which biopharma companies must apply to bring new drugs to patients, is resource-intensive, lengthy, and highly risky. Nine … Read more
We are excited to announce the availability of Gemma 3 27B Instruct models through Amazon Bedrock Marketplace and Amazon SageMaker JumpStart. With this launch, developers and data scientists can now deploy Gemma 3, a 27-billion-parameter language model, along with its specialized instruction-following versions, to help accelerate building, experimentation, and scalable deployment of generative AI solutions … Read more
Organizations today deal with vast amounts of unstructured data in various formats including documents, images, audio files, and video files. Often these documents are quite large, creating significant challenges such as slower processing times and increased storage costs. Extracting meaningful insights from these diverse formats in the past required complex processing pipelines and significant development … Read more
Foundation models (FMs) have revolutionised AI capabilities, but adopting them for specific business needs can be challenging. Organizations often struggle with balancing model performance, cost-efficiency, and the need for domain-specific knowledge. This blog post explores three powerful techniques for tailoring FMs to your unique requirements: Retrieval Augmented Generation (RAG), fine-tuning, and a hybrid approach combining … Read more
Large language models (LLMs) have revolutionized the way we interact with technology, but their widespread adoption has been blocked by high inference latency, limited throughput, and high costs associated with text generation. These inefficiencies are particularly pronounced during high-demand events like Amazon Prime Day, where systems like Rufus—the Amazon AI-powered shopping assistant—must handle massive scale … Read more
Organizations across a wide range of industries are struggling to process massive amounts of unstructured video and audio content to support their core business applications and organizational priorities. Amazon Bedrock Data Automation helps them meet this challenge by streamlining application development and automating workflows that use content from documents, images, audio, and video. Recently, we … Read more
This blog post is co-written with Heidi Vogel Brockmann and Ronald Brockmann from GuardianGamer. Millions of families face a common challenge: how to keep children safe in online gaming without sacrificing the joy and social connection these games provide. In this post, we share how GuardianGamer—a member of the AWS Activate startup community—has built a … Read more
This post was cowritten by Mulay Ahmed, Assistant Director of Engineering, and Ruby Donald, Assistant Director of Engineering at Principal Financial Group. The content and opinions in this post are those of the third-party author and AWS is not responsible for the content or accuracy of this post. Principal Financial Group® is an integrated global … Read more
Improving response quality for user queries is essential for AI-driven applications, especially those focusing on user satisfaction. For example, an HR chat-based assistant should strictly follow company policies and respond using a certain tone. A deviation from that can be corrected by feedback from users. This post demonstrates how Amazon Bedrock, combined with a user … Read more
Amazon Q Business, with its enterprise grade security, seamless integration with multiple diverse data sources, and sophisticated natural language understanding, represents the next generation of AI business assistants. What sets Amazon Q Business apart is its support of enterprise requirements from its ability to integrate with company documentation to its adaptability with specific business terminology … Read more
As companies increasingly adopt generative AI applications, AI agents capable of delivering tangible business value have emerged as a crucial component. In this context, integrating custom-built AI agents within chat services such as Slack can be transformative, providing businesses with seamless access to AI assistants powered by sophisticated foundation models (FMs). After an AI agent … Read more
Data privacy is a critical issue for software companies that provide services in the data management space. If they want customers to trust them with their data, software companies need to show and prove that their customers’ data will remain confidential and within controlled environments. Some companies go to great lengths to maintain confidentiality, sometimes … Read more
Enterprises—especially in the insurance industry—face increasing challenges in processing vast amounts of unstructured data from diverse formats, including PDFs, spreadsheets, images, videos, and audio files. These might include claims document packages, crash event videos, chat transcripts, or policy documents. All contain critical information across the claims processing lifecycle. Traditional data preprocessing methods, though functional, might … Read more
In the mortgage servicing industry, efficient document processing can mean the difference between business growth and missed opportunities. This post explores how Onity Group, a financial services company specializing in mortgage servicing and origination, used Amazon Bedrock and other AWS services to transform their document processing capabilities. Onity Group, founded in 1988, is headquartered in … Read more
This blog post is co-written with Jonas Neuman from HERE Technologies. HERE Technologies, a 40-year pioneer in mapping and location technology, collaborated with the AWS Generative AI Innovation Center (GenAIIC) to enhance developer productivity with a generative AI-powered coding assistant. This innovative tool is designed to enhance the onboarding experience for HERE’s self-service Maps API … Read more
Businesses are constantly evolving, and leaders are challenged every day to meet new requirements and are seeking ways to optimize their operations and gain a competitive edge. One of the key challenges they face is managing the complexity of disparate business systems and workflows, which leads to inefficiencies, data silos, and missed opportunities. Generative AI … Read more
With the rise of generative AI and knowledge extraction in AI systems, Retrieval Augmented Generation (RAG) has become a prominent tool for enhancing the accuracy and reliability of AI-generated responses. RAG is as a way to incorporate additional data that the large language model (LLM) was not trained on. This can also help reduce generation … Read more
As one of the fastest sports in the world, almost everything is a race in Formula 1® (F1), even the pit stops. F1 drivers need to stop to change tires or make repairs to damage sustained during a race. Each precious tenth of a second the car is in the pit is lost time in … Read more
This post is co-authored by Manuel Lopez Roldan, SiMa.ai, and Jason Westra, AWS Senior Solutions Architect. Are you looking to deploy machine learning (ML) models at the edge? With Amazon SageMaker AI and SiMa.ai’s Palette Edgematic platform, you can efficiently build, train, and deploy optimized ML models at the edge for a variety of use … Read more
This post is co-written with Ken Tsui, Edward Tsoi and Mickey Yip from Apoidea Group. The banking industry has long struggled with the inefficiencies associated with repetitive processes such as information extraction, document review, and auditing. These tasks, which require significant human resources, slow down critical operations such as Know Your Customer (KYC) procedures, loan … Read more
This post is co-authored by Jay Kshirsagar and Ronald Quan from Qualtrics. The content and opinions in this post are those of the third-party author and AWS is not responsible for the content or accuracy of this post. Qualtrics, founded in 2002, is a pioneering software company that has spent over two decades creating exceptional … Read more
Vxceed delivers SaaS solutions across industries such as consumer packaged goods (CPG), transportation, and logistics. Its modular environments include Lighthouse for CPG demand and supply chains, GroundCentric247 for airline and airport operations, and LimoConnect247 and FleetConnect247 for passenger transport. These solutions support a wide range of customers, including government agencies in Australia and New Zealand. … Read more