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Build a drug discovery research assistant using Strands Agents and Amazon Bedrock

Advanced (300), Amazon Bedrock, Artificial Intelligence, Life Sciences, Technical How-to /

Drug discovery is a complex, time-intensive process that requires researchers to navigate vast amounts of scientific literature, clinical trial data, and molecular databases. Life science customers like Genentech and AstraZeneca are using AI agents and other generative AI tools to increase the speed of scientific discovery. Builders at these organizations are already using the fully […]

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Build an intelligent eDiscovery solution using Amazon Bedrock Agents

Amazon Bedrock, Amazon Bedrock Agents, Best Practices, Customer Solutions, Generative AI, Technical How-to /

Legal teams spend bulk of their time manually reviewing documents during eDiscovery. This process involves analyzing electronically stored information across emails, contracts, financial records, and collaboration systems for legal proceedings. This manual approach creates significant bottlenecks: attorneys must identify privileged communications, assess legal risks, extract contractual obligations, and maintain regulatory compliance across thousands of documents

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Benchmarking Amazon Nova: A comprehensive analysis through MT-Bench and Arena-Hard-Auto

Advanced (300), AI/ML, Amazon Bedrock, Amazon Machine Learning, Amazon Nova, Generative AI, Technical How-to /

Large language models (LLMs) have rapidly evolved, becoming integral to applications ranging from conversational AI to complex reasoning tasks. However, as models grow in size and capability, effectively evaluating their performance has become increasingly challenging. Traditional benchmarking metrics like perplexity and BLEU scores often fail to capture the nuances of real-world interactions, making human-aligned evaluation

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Multi-tenant RAG implementation with Amazon Bedrock and Amazon OpenSearch Service for SaaS using JWT

Advanced (300), Amazon Bedrock, Amazon Bedrock Knowledge Bases, Amazon OpenSearch Service, Technical How-to /

In recent years, the emergence of large language models (LLMs) has accelerated AI adoption across various industries. However, to further augment LLMs’ capabilities and effectively use up-to-date information and domain-specific knowledge, integration with external data sources is essential. Retrieval Augmented Generation (RAG) has gained attention as an effective approach to address this challenge. RAG is

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Use generative AI in Amazon Bedrock for enhanced recommendation generation in equipment maintenance

Amazon Bedrock, Amazon Bedrock Knowledge Bases, Amazon Nova, Amazon SageMaker Ground Truth, Experience-Based Acceleration, Generative AI, Manufacturing, Recommendation Engine, Technical How-to /

In the manufacturing world, valuable insights from service reports often remain underutilized in document storage systems. This post explores how Amazon Web Services (AWS) customers can build a solution that automates the digitisation and extraction of crucial information from many reports using generative AI. The solution uses Amazon Nova Pro on Amazon Bedrock and Amazon

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Build an AI-powered automated summarization system with Amazon Bedrock and Amazon Transcribe using Terraform

Amazon Bedrock, Amazon Machine Learning, Amazon Transcribe, Artificial Intelligence, Technical How-to /

Extracting meaningful insights from unstructured data presents significant challenges for many organizations. Meeting recordings, customer interactions, and interviews contain invaluable business intelligence that remains largely inaccessible due to the prohibitive time and resource costs of manual review. Organizations frequently struggle to efficiently capture and use key information from these interactions, resulting in not only productivity

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Build real-time travel recommendations using AI agents on Amazon Bedrock

Amazon Bedrock, Amazon Bedrock Agents, Amazon Bedrock Knowledge Bases, Technical How-to /

Generative AI is transforming how businesses deliver personalized experiences across industries, including travel and hospitality. Travel agents are enhancing their services by offering personalized holiday packages, carefully curated for customer’s unique preferences, including accessibility needs, dietary restrictions, and activity interests. Meeting these expectations requires a solution that combines comprehensive travel knowledge with real-time pricing and

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Manage multi-tenant Amazon Bedrock costs using application inference profiles

Amazon Bedrock, Technical How-to /

Successful generative AI software as a service (SaaS) systems require a balance between service scalability and cost management. This becomes critical when building a multi-tenant generative AI service designed to serve a large, diverse customer base while maintaining rigorous cost controls and comprehensive usage monitoring. Traditional cost management approaches for such systems often reveal limitations.

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Amazon Bedrock Knowledge Bases now supports Amazon OpenSearch Service Managed Cluster as vector store

Advanced (300), Amazon Bedrock, Amazon Bedrock Knowledge Bases, Amazon OpenSearch Service, Artificial Intelligence, Generative AI, Technical How-to /

Amazon Bedrock Knowledge Bases has extended its vector store options by enabling support for Amazon OpenSearch Service managed clusters, further strengthening its capabilities as a fully managed Retrieval Augmented Generation (RAG) solution. This enhancement builds on the core functionality of Amazon Bedrock Knowledge Bases , which is designed to seamlessly connect foundation models (FMs) with

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Monitor agents built on Amazon Bedrock with Datadog LLM Observability

Amazon Bedrock Agents, DevOps, Intermediate (200), Monitoring and observability, Partner solutions, Technical How-to /

This post was co-written with Mohammad Jama, Yun Kim, and Barry Eom from Datadog. The emergence of generative AI agents in recent years has transformed the AI landscape, driven by advances in large language models (LLMs) and natural language processing (NLP). The focus is shifting from simple AI assistants to Agentic AI systems that can

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