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Today, we’re sharing how Amazon Bedrock makes it straightforward to customize Amazon Nova models for your specific business needs. As customers scale their AI deployments, they need models that reflect proprietary knowledge and workflows — whether that means maintaining a consistent brand voice in customer communications, handling complex industry-specific workflows or accurately classifying intents in …

Customize Amazon Nova models with Amazon Bedrock fine-tuning Read More »

In healthcare and life sciences, AI agents help organizations process clinical data, submit regulatory filings, automate medical coding, and accelerate drug development and commercialization. However, the sensitive nature of healthcare data and regulatory requirements like Good Practice (GxP) compliance require human oversight at key decision points. This is where human-in-the-loop (HITL) constructs become essential. In …

Human-in-the-loop constructs for agentic workflows in healthcare and life sciences Read More »

If you’re looking to enhance your content understanding and search capabilities, audio embeddings offer a powerful solution. In this post, you’ll learn how to use Amazon Nova Multimodal Embeddings to transform your audio content to searchable, intelligent data that captures acoustic features like tone, emotion, musical characteristics, and environmental sounds. Finding specific content in these …

Building intelligent audio search with Amazon Nova Embeddings: A deep dive into semantic audio understanding Read More »

You can use reinforcement Fine-Tuning (RFT) in Amazon Bedrock to customize Amazon Nova and supported open source models by defining what “good” looks like—no large labeled datasets required. By learning from reward signals rather than static examples, RFT delivers up to 66% accuracy gains over base models at reduced customization cost and complexity. This post …

Reinforcement fine-tuning on Amazon Bedrock: Best practices Read More »

As organizations scale their AI workloads on Amazon Bedrock, understanding what’s driving spending becomes critical. Teams might need to perform chargebacks, investigate cost spikes, and guide optimization decisions, all of which require cost attribution at the workload level. With Amazon Bedrock Projects, you can attribute inference costs to specific workloads and analyze them in AWS …

Manage AI costs with Amazon Bedrock Projects Read More »

Content creators and organizations today face a persistent challenge: producing high-quality audio content at scale. Traditional podcast production requires significant time investment (research, scheduling, recording, editing) and substantial resources including studio space, equipment, and voice talent. These constraints limit how quickly organizations can respond to new topics or scale their content production. Amazon Nova 2 …

Building real-time conversational podcasts with Amazon Nova 2 Sonic Read More »

Building a text-to-SQL solution using Amazon Bedrock can alleviate one of the most persistent bottlenecks in data-driven organizations: the delay between asking a business question and getting a clear, data-backed answer. You might be familiar with the challenge of navigating competing priorities when your one-time question is waiting in the queue behind higher-impact work. A text-to-SQL …

Text-to-SQL solution powered by Amazon Bedrock Read More »

Enterprises often struggle to onboard new team members at scale. Human resources (HR) teams spend time on manual tasks that delay productivity, such as processing documents to answering repeated questions about benefits and policies. For organizations with many new hires, these steps make it harder to keep onboarding consistent and compliant. Organizations lose substantial amounts …

Build AI-powered employee onboarding agents with Amazon Quick Read More »

Agentic tool calling is what makes AI agents useful in production. It’s how they query databases, trigger workflows, retrieve real-time data, and act on a user’s behalf. But base models frequently hallucinate tools, pass bad parameters, and attempt actions when they should ask for clarification. These failures erode trust and block production deployment. You can …

Accelerate agentic tool calling with serverless model customization in Amazon SageMaker AI Read More »

Agentic generative AI assistants represent a significant advancement in artificial intelligence, featuring dynamic systems powered by large language models (LLMs) that engage in open-ended dialogue and tackle complex tasks. Unlike basic chatbots, these implementations possess broad intelligence, maintaining multi-step conversations while adapting to user needs and executing necessary backend tasks. These systems retrieve business-specific data …

Building Intelligent Search with Amazon Bedrock and Amazon OpenSearch for hybrid RAG solutions Read More »