Design patterns for scalable voice agents matter for organizations that need to deliver fast, natural, and reliable voice experiences. Many teams face challenges like high latency, managing real-time audio, and coordinating multiple agents in complex workflows. In this post, you’ll learn how to use Amazon Nova Sonic, Amazon Bedrock AgentCore, and Strands BidiAgent to build …
Agentic IDEs that forget what you told them in previous sessions aren’t very helpful. You work on your large codebase with complex business requirements for days or weeks. However, your IDE only remembers you during your current session and can’t recall your conversational history, preferences derived from the conversations, or additional insights. You end up …
Extending conversational memory in Kiro CLI using Amazon Bedrock AgentCore Memory Read More »
Amazon SageMaker Feature Store is a fully managed, purpose-built repository to store, share, and manage features for machine learning (ML) models. It now supports Apache Iceberg table format, streaming ingestion, scalable batch ingestion, and fine-grained access control through AWS Lake Formation. As organizations scale their machine learning platforms from experimentation to production, two operational challenges …
Accelerate ML feature pipelines with new capabilities in Amazon SageMaker Feature Store Read More »
Programmatic tool calling (PTC) is a paradigm shift in how large language models (LLMs) interact with external tools. In a traditional tool-calling workflow, each tool invocation requires a full round trip back to the model. The model calls a tool, receives the result, reasons about it, calls the next tool, and so on. For workflows …
Implementing programmatic tool calling on Amazon Bedrock Read More »
If you moderate user-generated content at scale, you need a system that catches policy violations accurately without over-flagging legitimate posts. A moderation system that misses harmful content puts you at risk, while one that flags too aggressively frustrates your audience. Every organization defines its own policies, so a single classifier rarely works for every use …
This guest post is co-written by Angela Mapes and Adam Walker of Aderant. Aderant, a leading global provider of comprehensive business management software for the legal industry, transformed how its 38-person Cloud Engineering team supports Expert Sierra, its cloud-based legal practice management solution. By implementing Amazon Quick, Aderant has accelerated documentation processes and empowered its …
Aderant transforms cloud operations with Amazon Quick Read More »
Teams can integrate Atlassian Confluence Cloud with Amazon Quick to search and manage documentation without switching between multiple systems. When documentation lives in Confluence, but related data sits in other systems, teams waste time switching tools, re-searching for context, and manually gathering information. These interruptions slow decisions and create gaps between available knowledge and actionable …
Integrate Atlassian Confluence Cloud with Amazon Quick Read More »
Special thanks to everyone who contributed to this launch: Stephanie Yuan, Lefan Zhang, Ritvika Pillai, Irene Wang, Carter Williams, T.J Ariyawansa, Gitika Jha, Shoaib Javed and the product leadership from Vivek Singh. Moving prototype agents to production requires measuring quality across multiple dimensions. Amazon Bedrock AgentCore Evaluations provides large language model (LLM)-as-a-Judge checks and extensible …
Build custom code-based evaluators in Amazon Bedrock AgentCore Read More »
Organizations that must restrict access to sensitive documents increasingly rely on AI-driven search and chat to help employees find answers across large repositories. Coarse-grained permissions that control access at the knowledge base level work well for many teams, but sensitive documents require more granular control to restrict specific documents or folders to authorized teams, individuals, …
Improving bot accuracy in Amazon Lex starts with handling how customers communicate naturally. Your customers express the same request in dozens of different ways, combine multiple pieces of information in one sentence, and often speak ambiguously. The Assisted NLU (natural language understanding) feature in Amazon Lex helps you improve bot accuracy by handling these natural …
Improve bot accuracy with Amazon Lex Assisted NLU Read More »
