[AI]Amazon Bedrock gains new AI models, tools, and features

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(AWS) has announced improvements to bolster Bedrock, its fully managed generative AI service.

The updates include new foundational models from several AI pioneers, enhanced data processing capabilities, and features aimed at improving inference efficiency.

Dr Swami Sivasubramanian, VP of AI and Data at AWS, said: “

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Bedrock continues to see rapid growth as customers flock to the service for its broad selection of leading models, tools to easily customise with their data, built-in responsible AI features, and capabilities for developing sophisticated agents.

“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.”

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Bedrock expands its model diversity

AWS is set to become the first cloud provider to feature models from AI developers Luma AI and poolside, while also incorporating Stability AI’s latest release.

Through its new

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Bedrock Marketplace, customers will have access to over 100 emerging and specialised models from across industries, ensuring they can select the most appropriate tools for their unique needs.

• Luma AI’s Ray 2 

Luma AI, known for advancing generative AI in video content creation, brings its next-generation Ray 2 model to

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Bedrock. This model generates high-quality, lifelike video outputs from text or image inputs and allows organisations to create detailed outputs in fields such as fashion, architecture, and graphic design. AWS’s presence as the first provider for this model ensures businesses can experiment with new camera angles, cinematographic styles, and consistent characters with a frictionless workflow.

• poolside’s malibu and point

Designed to address challenges in modern software engineering, poolside’s models – malibu and point – specialise in code generation, testing, documentation, and real-time code completion. Importantly, developers can securely fine-tune these models using their private datasets. Accompanied by Assistant – an integration for development environments – poolside’s tools allow engineering teams to accelerate productivity, ship projects faster, and increase accuracy.

• Stability AI’s Stable Diffusion 3.5 Large  

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Bedrock customers will soon gain access to Stability AI’s text-to-image model

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. This addition supports businesses in creating high-quality visual media for use cases in areas like gaming, advertising, and retail.  

Through the Bedrock Marketplace, AWS also enables access to over 100 specialised models. These include solutions tailored to fields such as biology (EvolutionaryScale’s ESM3 generative model), financial data (Writer’s Palmyra-Fin), and media (Camb.ai’s text-to-audio MARS6).

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Zendesk, a global customer service software firm, leverages Bedrock’s marketplace to personalise support across email and social channels using AI-driven localisation and sentiment analysis tools. For example, they use models like Widn.AI to tailor responses based on real-time sentiment in customers’ native languages.

Scaling inference with new

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Bedrock features

Large-scale generative AI applications require balancing the cost, latency, and accuracy of inference processes. AWS is addressing this challenge with two new

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Bedrock features:

• Prompt Caching

The new caching capability reduces redundant processing of prompts by securely storing frequently used queries, saving on both time and costs. This feature can lead to up to a 90% reduction in costs and an 85% decrease in latency. For example,

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incorporated Prompt Caching into its Acrobat AI Assistant to summarise documents and answer questions, achieving a 72% reduction in response times during initial testing.  

• Intelligent Prompt Routing

This feature dynamically directs prompts to the most suitable foundation model within a family, optimising results for both cost and quality. Customers such as Argo Labs, which builds conversational voice AI solutions for restaurants, have already benefited. While simpler queries (like booking tables) are handled by smaller models, more nuanced requests (e.g., dietary-specific menu questions) are intelligently routed to larger models. Argo Labs’ usage of intelligent Prompt Routing has not only improved response quality but also reduced costs by up to 30%.

Data utilisation: Knowledge bases and automation

A key attraction of generative AI lies in its ability to extract value from data. AWS is enhancing its

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Bedrock Knowledge Bases to ensure organisations can deploy their unique datasets for richer AI-powered user experiences.  

• Using structured data 

AWS has introduced capabilities for structured data retrieval within Knowledge Bases. This enhancement allows customers to query data stored across

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services like SageMaker Lakehouse and Redshift through natural-language prompts, with results translated back into SQL queries. Octus, a credit intelligence firm, plans to use this capability to provide clients with dynamic, natural-language reports on its structured financial data.  

• GraphRAG integration 

By incorporating automated graph modelling (powered by

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Neptune), customers can now generate and connect relational data for stronger AI applications. BMW Group, for instance, will use GraphRAG to augment its virtual assistant MAIA. This assistant taps into BMW’s wealth of internal data to deliver comprehensive responses and premium user experiences.

Separately, AWS has unveiled

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Bedrock Data Automation, a tool that transforms unstructured content (e.g., documents, video, and audio) into structured formats for analytics or retrieval-augmented generation (RAG). Companies like Symbeo (automated claims processing) and Tenovos (digital asset management) are already piloting the tool to improve operational efficiency and data reuse.

The expansion of

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Bedrock’s ecosystem reflects its growing popularity, with the service recording a 4.7x increase in its customer base over the last year. Industry leaders like

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, BMW, Zendesk, and Tenovos have all embraced AWS’s latest innovations to improve their generative AI capabilities.  

Most of the newly announced tools – such as inference management, Knowledge Bases with structured data retrieval, and GraphRAG – are currently in preview, while notable model releases from Luma AI, poolside, and Stability AI are expected soon.

See also:

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