Artificial Intelligence
Accelerate AI development with Amazon Bedrock API keys
Today, we’re excited to announce a significant improvement to the developer experience of Amazon Bedrock: API keys. API keys provide quick access to the Amazon Bedrock APIs, streamlining the authentication process so that developers can focus on building rather than configuration.
Accelerating data science innovation: How Bayer Crop Science used AWS AI/ML services to build their next-generation MLOps service
In this post, we show how Bayer Crop Science manages large-scale data science operations by training models for their data analytics needs and maintaining high-quality code documentation to support developers. Through these solutions, Bayer Crop Science projects up to a 70% reduction in developer onboarding time and up to a 30% improvement in developer productivity.
Combat financial fraud with GraphRAG on Amazon Bedrock Knowledge Bases
In this post, we show how to use Amazon Bedrock Knowledge Bases GraphRAG with Amazon Neptune Analytics to build a financial fraud detection solution.
Classify call center conversations with Amazon Bedrock batch inference
In this post, we demonstrate how to build an end-to-end solution for text classification using the Amazon Bedrock batch inference capability with the Anthropic’s Claude Haiku model. We walk through classifying travel agency call center conversations into categories, showcasing how to generate synthetic training data, process large volumes of text data, and automate the entire workflow using AWS services.
Effective cross-lingual LLM evaluation with Amazon Bedrock
In this post, we demonstrate how to use the evaluation features of Amazon Bedrock to deliver reliable results across language barriers without the need for localized prompts or custom infrastructure. Through comprehensive testing and analysis, we share practical strategies to help reduce the cost and complexity of multilingual evaluation while maintaining high standards across global large language model (LLM) deployments.
Cohere Embed 4 multimodal embeddings model is now available on Amazon SageMaker JumpStart
The Cohere Embed 4 multimodal embeddings model is now generally available on Amazon SageMaker JumpStart. The Embed 4 model is built for multimodal business documents, has leading multilingual capabilities, and offers notable improvement over Embed 3 across key benchmarks. In this post, we discuss the benefits and capabilities of this new model. We also walk you through how to deploy and use the Embed 4 model using SageMaker JumpStart.
How INRIX accelerates transportation planning with Amazon Bedrock
INRIX pioneered the use of GPS data from connected vehicles for transportation intelligence. In this post, we partnered with Amazon Web Services (AWS) customer INRIX to demonstrate how Amazon Bedrock can be used to determine the best countermeasures for specific city locations using rich transportation data and how such countermeasures can be automatically visualized in street view images. This approach allows for significant planning acceleration compared to traditional approaches using conceptual drawings.
Qwen3 family of reasoning models now available in Amazon Bedrock Marketplace and Amazon SageMaker JumpStart
Today, we are excited to announce that Qwen3, the latest generation of large language models (LLMs) in the Qwen family, is available through Amazon Bedrock Marketplace and Amazon SageMaker JumpStart. With this launch, you can deploy the Qwen3 models—available in 0.6B, 4B, 8B, and 32B parameter sizes—to build, experiment, and responsibly scale your generative AI applications on AWS. In this post, we demonstrate how to get started with Qwen3 on Amazon Bedrock Marketplace and SageMaker JumpStart.
Build a just-in-time knowledge base with Amazon Bedrock
Traditional Retrieval Augmented Generation (RAG) systems consume valuable resources by ingesting and maintaining embeddings for documents that might never be queried, resulting in unnecessary storage costs and reduced system efficiency. This post presents a just-in-time knowledge base solution that reduces unused consumption through intelligent document processing. The solution processes documents only when needed and automatically removes unused resources, so organizations can scale their document repositories without proportionally increasing infrastructure costs.
Agents as escalators: Real-time AI video monitoring with Amazon Bedrock Agents and video streams
In this post, we show how to build a fully deployable solution that processes video streams using OpenCV, Amazon Bedrock for contextual scene understanding and automated responses through Amazon Bedrock Agents. This solution extends the capabilities demonstrated in Automate chatbot for document and data retrieval using Amazon Bedrock Agents and Knowledge Bases, which discussed using Amazon Bedrock Agents for document and data retrieval. In this post, we apply Amazon Bedrock Agents to real-time video analysis and event monitoring.