Amazon Bedrock Empowers Customers to Accelerate Generative AI Adoption with More Than 100 New Models and Powerful New Capabilities for Inference and Working with Data
Amazon Web Services (AWS) announced major expansions to Amazon Bedrock, its managed service for generative AI applications. The updates include: access to over 100 new models through Amazon Bedrock Marketplace, new models from Luma AI, poolside, and Stability AI, and enhanced inference optimization tools.
Key innovations include prompt caching (reducing costs by up to 90% and latency by up to 85%), Intelligent Prompt Routing (cutting costs by up to 30%), and new data capabilities. The service introduced support for structured data retrieval and GraphRAG in Knowledge Bases, plus Amazon Bedrock Data Automation for transforming unstructured data.
The platform has seen significant growth, with its customer base increasing 4.7x in the last year. Major companies including Adobe, BMW Group, and Zendesk are already implementing these new features.
Amazon Web Services (AWS) ha annunciato importanti espansioni per Amazon Bedrock, il suo servizio gestito per applicazioni di intelligenza artificiale generativa. Gli aggiornamenti includono: accesso a oltre 100 nuovi modelli tramite il Marketplace di Amazon Bedrock, nuovi modelli da Luma AI, poolside e Stability AI, e strumenti ottimizzati per l'inferenza.
Le principali innovazioni comprendono la memorizzazione delle richieste (che riduce i costi fino al 90% e la latenza fino all'85%), il Routing Intelligente delle Richieste (che taglia i costi fino al 30%) e nuove capacità di gestione dei dati. Il servizio ha introdotto il supporto per il recupero di dati strutturati e GraphRAG nelle Basi di Conoscenza, oltre ad Amazon Bedrock Data Automation per la trasformazione dei dati non strutturati.
La piattaforma ha registrato una crescita significativa, con la propria clientela aumentata di 4,7 volte nell'ultimo anno. Grandi aziende come Adobe, BMW Group e Zendesk stanno già implementando queste nuove funzionalità.
Amazon Web Services (AWS) anunció importantes expansiones para Amazon Bedrock, su servicio gestionado para aplicaciones de inteligencia artificial generativa. Las actualizaciones incluyen: acceso a más de 100 nuevos modelos a través del Marketplace de Amazon Bedrock, nuevos modelos de Luma AI, poolside y Stability AI, y herramientas de optimización de inferencia mejoradas.
Las principales innovaciones incluyen almacenamiento en caché de solicitudes (reduciendo costos hasta en un 90% y latencia hasta un 85%), Enrutamiento Inteligente de Solicitudes (reduciendo costos hasta en un 30%) y nuevas capacidades de datos. El servicio introdujo soporte para la recuperación de datos estructurados y GraphRAG en Bases de Conocimiento, además de Amazon Bedrock Data Automation para transformar datos no estructurados.
La plataforma ha visto un crecimiento significativo, con su base de clientes aumentando 4.7 veces en el último año. Empresas importantes, incluyendo Adobe, BMW Group y Zendesk, ya están implementando estas nuevas características.
아마존 웹 서비스(AWS)는 생성적 AI 애플리케이션을 위한 관리형 서비스인 아마존 베드록의 주요 확장을 발표했습니다. 업데이트에는 아마존 베드록 마켓플레이스를 통해 100개 이상의 새로운 모델에 대한 접근과 Luma AI, poolside 및 Stability AI의 새로운 모델, 그리고 개선된 추론 최적화 도구가 포함됩니다.
주요 혁신에는 요청 캐싱(비용 최대 90%, 대기 시간 최대 85% 감소), 지능형 요청 라우팅(비용 최대 30% 절감), 그리고 새로운 데이터 기능이 포함됩니다. 이 서비스는 구조화된 데이터 검색 지원과 지식 기반의 GraphRAG, 비구조화된 데이터를 변환하기 위한 아마존 베드록 데이터 자동화도 도입했습니다.
이 플랫폼은 значительным ростом을 보였으며, 고객 수가 지난 1년간 4.7배 증가했습니다. Adobe, BMW 그룹 및 Zendesk와 같은 주요 기업들이 이미 이러한 새로운 기능을 구현하고 있습니다.
Amazon Web Services (AWS) a annoncé d'importantes extensions pour Amazon Bedrock, son service géré pour les applications d'IA générative. Les mises à jour incluent : un accès à plus de 100 nouveaux modèles via le Marketplace d'Amazon Bedrock, de nouveaux modèles provenant de Luma AI, poolside et Stability AI, ainsi que des outils d'optimisation de l'inférence améliorés.
Les innovations clés comprennent la mise en cache des invites (réduisant les coûts jusqu'à 90 % et la latence jusqu'à 85 %), le routage intelligent des invites (réduisant les coûts jusqu'à 30 %) et de nouvelles capacités de données. Le service a introduit le support pour la récupération de données structurées et GraphRAG dans les Bases de Connaissances, ainsi qu'Amazon Bedrock Data Automation pour transformer des données non structurées.
La plateforme a connu une croissance significative, avec sa base de clients augmentant de 4,7 fois l'année dernière. Des entreprises majeures telles qu'Adobe, le groupe BMW et Zendesk mettent déjà en œuvre ces nouvelles fonctionnalités.
Amazon Web Services (AWS) hat bedeutende Erweiterungen für Amazon Bedrock, seinen verwalteten Dienst für generative KI-Anwendungen, angekündigt. Zu den Updates gehören: Zugang zu über 100 neuen Modellen über den Amazon Bedrock Marketplace, neue Modelle von Luma AI, poolside und Stability AI sowie verbesserte Optimierungstools für die Inferenz.
Wichtige Innovationen sind unter anderem die Aufforderungscaching (die Kosten um bis zu 90% und die Latenz um bis zu 85% reduziert), intelligentes Aufforderungsrouting (Kosten um bis zu 30% senkend) und neue Datenfähigkeiten. Der Dienst hat Unterstützung für die Abfrage strukturierter Daten und GraphRAG in Wissensdatenbanken sowie Amazon Bedrock Data Automation zur Umwandlung unstrukturierter Daten eingeführt.
Die Plattform hat ein signifikantes Wachstum erlebt, wobei die Kundenbasis im letzten Jahr um das 4,7-fache gewachsen ist. Bedeutende Unternehmen wie Adobe, die BMW Group und Zendesk setzen diese neuen Funktionen bereits um.
- Customer base growth of 4.7x in the last year indicates strong market adoption
- Prompt caching reduces costs by up to 90% and latency by up to 85%
- Intelligent Prompt Routing can reduce costs by up to 30%
- Expansion of model offerings provides greater flexibility and competitive advantage
- None.
Insights
The expansion of Amazon Bedrock represents a significant strategic move in AWS's AI infrastructure offerings. The addition of over 100 new models and the launch of Bedrock Marketplace positions AWS as a dominant force in the enterprise AI space. Key technical advancements include:
- Prompt caching capability reducing costs by up to
90% and latency by up to85% - Intelligent Prompt Routing delivering up to
30% cost reduction - Integration of premium models from Luma AI, poolside and Stability AI
- New structured data support and GraphRAG capabilities enhancing data utilization
The platform's
This development has substantial market implications for AWS's cloud computing dominance and revenue potential. The new capabilities address critical enterprise needs for AI deployment, particularly cost optimization and data integration. The introduction of Bedrock Marketplace creates a new ecosystem that could generate significant recurring revenue through model deployment fees and usage charges.
The partnership with specialized AI providers like Luma AI and poolside demonstrates AWS's strategy to capture various industry verticals, from creative content to software development. The focus on cost reduction features while expanding capabilities shows AWS's commitment to enterprise-scale AI adoption, which could accelerate their market share growth in the rapidly expanding enterprise AI sector.
The biggest expansion of models to date, new inference optimization tools, and additional data capabilities give customers even greater flexibility and control to build and deploy production-ready generative AI faster
Discover Amazon Bedrock Marketplace models and Amazon Bedrock fully managed models in the new model catalog (Graphic: Business Wire)
- AWS will soon be the first cloud provider to offer models from Luma AI and poolside. AWS will also add the latest Stability AI model in Amazon Bedrock and, through the new Amazon Bedrock Marketplace capability, is giving access to more than 100 popular, emerging, and specialized models, so customers can find the right set of models for their use case.
- New prompt caching and Amazon Bedrock Intelligent Prompt Routing help customers more easily and cost effectively scale inference.
- Support for structured data and GraphRAG in Amazon Bedrock Knowledge Bases further expands how customers can leverage their data to deliver customized generative AI experiences.
- Amazon Bedrock Data Automation automatically transforms unstructured, multimodal data into structured data with no coding required—helping customers use more of their data for generative AI and analytics.
- Tens of thousands of customers trust Amazon Bedrock to run their generative AI applications as the service has grown its customer base by 4.7x in the last year. Adobe, Argo Labs, BMW Group, Octus, Symbeo, Tenovos, and Zendesk are already adopting the latest Amazon Bedrock advancements.
“Amazon Bedrock continues to see rapid growth as customers flock to the service for its broad selection of leading models, tools to easily customize with their data, built-in responsible AI features, and capabilities for developing sophisticated agents,” said Dr. Swami Sivasubramanian, vice president of AI and Data at AWS. “Amazon Bedrock is helping to tackle the biggest roadblocks developers face today, so customers can realize the full potential of generative AI. With this new set of capabilities, we are empowering customers to develop more intelligent AI applications that will deliver greater value to their end users.”
The broadest selection of models from leading AI companies
Amazon Bedrock provides customers with the broadest selection of fully managed models from leading AI companies, including AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, and Stability AI. Additionally, Amazon Bedrock is the only place customers can access the newly announced Amazon Nova models, a new generation of foundation models that deliver state-of-the-art intelligence across a wide range of tasks and industry-leading price performance. With today’s announcements, AWS is further expanding model choice in Amazon Bedrock with the addition of more industry-leading models.
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Luma AI’s Ray 2: Luma AI’s multimodal models and software products advance video content creation with generative AI. AWS will be the first cloud provider to make Luma AI’s state-of-the-art Luma Ray 2 model, the second generation of its renowned video model, available to customers. Ray
2 marks a significant advancement in generative AI-assisted video creation, generating high-quality, realistic videos from text and images with efficiency and cinematographic quality. Customers can rapidly experiment with different camera angles and styles, create videos with consistent characters and accurate physics, and deliver creative outputs for architecture, fashion, film, graphic design, and music. - poolside’s malibu and point: poolside addresses the challenges of modern software engineering for large enterprises. AWS will be the first cloud provider to offer access to poolside’s malibu and point models, which excel at code generation, testing, documentation, and real-time code completion. This empowers engineering teams to improve productivity, write better code faster, and accelerate product development cycles. Both models can also be fine-tuned securely and privately on customers’ codebases, practices, and documentation, enabling them to adapt to specific projects and helping customers tackle daily software engineering tasks with increased accuracy and efficiency. Additionally, AWS will be the first cloud provider to offer access to poolside’s Assistant, which puts the power of poolside’s malibu and point models inside of developers' preferred integrated development environments (IDEs).
- Stability AI’s Stable Diffusion 3.5 Large: Stability AI is a leading generative AI model developer in visual media, with cutting-edge models in image, video, 3D, and audio. Amazon Bedrock will soon add Stable Diffusion 3.5 Large, Stability AI’s most advanced text-to-image model. This new model generates high-quality images from text descriptions in a wide range of styles to accelerate the creation of concept art, visual effects, and detailed product imagery for customers in media, gaming, advertising, and retail.
Access more than 100 popular, emerging, and specialized models with Amazon Bedrock Marketplace
While the models in Amazon Bedrock can support a wide range of tasks, many customers want to incorporate emerging and specialized models into their applications to power unique use cases, like analyzing a financial document or generating novel proteins. With Amazon Bedrock Marketplace, customers can now easily find and choose from more than 100 models that can be deployed on AWS and accessed through a unified experience in Amazon Bedrock. This includes popular models such as Mistral AI’s Mistral NeMo Instruct 2407, Technology Innovation Institute’s Falcon RW 1B, and NVIDIA NIM microservices, along with a wide array of specialized models, including Writer’s Palmyra-Fin for the financial industry, Upstage’s Solar Pro for translation, Camb.ai’s text-to-audio MARS6, and EvolutionaryScale’s ESM3 generative model for biology.
Once a customer finds a model they want, they select the appropriate infrastructure for their scaling needs and easily deploy on AWS through fully managed endpoints. Customers can then securely integrate the model with Amazon Bedrock’s unified application programming interfaces (APIs), leverage tools like Guardrails and Agents, and benefit from built-in security and privacy features.
Zendesk is a global service software company with a diverse and multicultural customer base of 100,000 brands around the world. The company can use specialized models, like Widn.AI for translation, in Amazon Bedrock to personalize and localize customer service requests across email, chat, phone, and social media. This will provide agents with the data they need, such as sentiment or intent in the customer’s native language, to ultimately enhance the customer service experience.
Prompt caching and Intelligent Prompt Routing help customers tackle inference at scale
When selecting a model, developers need to balance multiple considerations, like accuracy, cost, and latency. Optimizing for any one of these factors can mean compromising on the others. To balance these considerations when deploying an application into production, customers employ a variety of techniques, like caching frequently used prompts or routing simple questions to smaller models. However, using these techniques is complex and time-consuming, requiring specialized expertise to iteratively test different approaches to ensure a good experience for end users. That is why AWS is adding two new capabilities to help customers more effectively manage prompts at scale.
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Lower response latency and costs by caching prompts: Amazon Bedrock can now securely cache prompts to reduce repeated processing, without compromising on accuracy. This can reduce costs by up to
90% and latency by up to85% for supported models. For example, a law firm could create a generative AI chat application that can answer lawyers’ questions about documents. When multiple lawyers ask questions about the same part of a document in their prompts, Amazon Bedrock could cache that section, so the section only gets processed once and can be reused each time someone wants to ask a question about it. This reduces the cost by shrinking the amount of information the model needs to process each time. Adobe’s Acrobat AI Assistant enhances user productivity by enabling quick document summarization and question answering. With prompt caching on Amazon Bedrock, Adobe observed a72% reduction in response time, based on preliminary testing. -
Intelligent Prompt Routing helps optimize response quality and cost: With Intelligent Prompt Routing, customers can configure Amazon Bedrock to automatically route prompts to different foundation models within a model family, helping them optimize for response quality and cost. Using advanced prompt matching and model understanding techniques, Intelligent Prompt Routing predicts the performance of each model for each request and dynamically routes requests to the model most likely to give the desired response at the lowest cost. Intelligent Prompt Routing can reduce costs by up to
30% without compromising on accuracy. Argo Labs, which delivers innovative voice agent solutions for restaurants, handles diverse customer inquiries and reservations with Intelligent Prompt Routing. As customers submit questions, place orders, and book tables, Argo Labs’ voice chatbot dynamically routes the query to the most suitable model, optimizing for both cost and quality of responses. For example, a simple yes-no question, like “Do you have an open table at this restaurant tonight?” could be handled by a smaller model, while a larger model could answer more complex questions such as, “What kind of vegan options does this restaurant provide?” With Intelligent Prompt Routing, Argo Labs can use their voice agents to seamlessly handle customer interactions, while achieving the right balance of accuracy and cost.
Two new capabilities for Amazon Bedrock Knowledge Bases help customers maximize the value of their data
Customers want to leverage their data, no matter where, or in what format, it resides to build unique generative AI-powered experiences for end users. Knowledge Bases is a fully managed capability that makes it easy for customers to customize foundation model responses with contextual and relevant data using retrieval augmented generation (RAG). While Knowledge Bases already makes it easy to connect to data sources like Amazon OpenSearch Serverless and Amazon Aurora, many customers have other data sources and data types they would like to incorporate into their generative AI applications. That is why AWS is adding two new capabilities to Knowledge Bases.
- Support for structured data retrieval accelerates generative AI app development: Knowledge Bases provides one of the first managed, out-of-the-box RAG solutions that enables customers to natively query their structured data where it resides for their generative AI applications. This capability helps break data silos across data sources, accelerating generative AI development from over a month to just days. Customers can build applications that use natural language queries to explore structured data stored in sources like Amazon SageMaker Lakehouse, Amazon S3 data lakes, and Amazon Redshift. With this new capability, prompts are translated into SQL queries to retrieve data results. Knowledge Bases automatically adjusts to a customer’s schema and data, learns from query patterns, and provides a range of customization options to further enhance the accuracy of their chosen use case. Octus, a credit intelligence company, will use the new structured data retrieval capability in Knowledge Bases to allow end users to query structured data using natural language. By connecting Knowledge Bases to Octus’ existing master data management system, end-user prompts can be translated into SQL queries that Amazon Bedrock uses to retrieve the relevant information and return it to the user as part of the application’s response. This will help Octus’ chatbots deliver precise, data-driven insights to its users and enhance the users’ interactions with the company’s array of data products.
- Support for GraphRAG generates more relevant responses: Knowledge graphs allow customers to model and store relationships between data by mapping different pieces of relevant information like a web. These knowledge graphs can be particularly useful when incorporated into RAG, allowing a system to easily traverse and retrieve relevant parts of information by following the graph. Now, with support for GraphRAG, Knowledge Bases can enable customers to automatically generate graphs using Amazon Neptune, AWS’s managed graph database, and link relationships between entities across data, without requiring any graph expertise. Knowledge Bases makes it easier to generate more accurate and relevant responses, identify related connections using the knowledge graph, and view the source information to understand how a model arrived at a specific response. BMW Group will implement GraphRAG for My AI Assistant (MAIA), an AI-powered virtual assistant that helps users find, understand, and integrate the company’s internal data assets hosted on AWS. With GraphRAG’s automated graph modeling powered by Amazon Neptune, BMW will be able to continuously update the knowledge graph powering MAIA based on data usage to provide more relevant and comprehensive insights from its data assets to continue creating premium experiences for millions of drivers.
Amazon Bedrock Data Automation transforms unstructured multimodal data into structured data for generative AI and analytics
Today, most enterprise data is unstructured and is contained in content like documents, videos, images, and audio files. Many customers want to take advantage of this data to discover insights or build new experiences for customers, but it is often a difficult, manual process to convert it into a format that can be easily used for analytics or RAG. For example, a bank may take in multiple PDF documents for loan processing and need to extract details from each one, normalize features like name or date of birth for consistency, and transform the results into a text-based format before entering them into a data warehouse to perform any analyses. With Amazon Bedrock Data Automation, customers can automatically extract, transform, and generate data from unstructured content at scale using a single API.
Amazon Bedrock Data Automation can quickly and cost effectively extract information from documents, images, audio, and videos and transform it into structured formats for use cases like intelligent document processing, video analysis, and RAG. Amazon Bedrock Data Automation can generate content using predefined defaults, like scene-by-scene descriptions of video stills or audio transcripts, or customers can create an output based on their own data schema that they can then easily load into an existing database or data warehouse. Through an integration with Knowledge Bases, Amazon Bedrock Data Automation can also be used to parse content for RAG applications, improving the accuracy and relevancy of results by including information embedded in both images and text. Amazon Bedrock Data Automation provides customers with a confidence score and grounds its responses in the original content, helping to mitigate the risk of hallucinations and increasing transparency.
Symbeo is a CorVel company that offers automated accounts payable solutions. The company will use Amazon Bedrock Data Automation to automate the extraction of data from complex documents, such as insurance claims, medical bills, and more. This will help Symbeo’s teams process claims faster and accelerate the turnaround time to get back to their customers. Tenovos, a digital asset management platform, is using Amazon Bedrock Data Automation to enable semantic search at scale to increase content reuse by
Amazon Bedrock Marketplace is available today. Inference management capabilities, structured data retrieval and GraphRAG in Amazon Bedrock Knowledge Bases, and Amazon Bedrock Data Automation are all available in preview. Models from Luma AI, poolside, and Stability AI are coming soon.
To learn more, visit:
- The AWS News Blog for details on today’s announcements: Amazon Bedrock Marketplace, prompt caching and Intelligent Prompt Routing, and data processing and retrieval capabilities.
- The Amazon Bedrock page to learn more about the capabilities.
- The Amazon Bedrock customer page to learn how companies are using Amazon Bedrock.
- The AWS re:Invent page for more details on everything happening at AWS re:Invent.
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