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Amazon Bedrock AgentCore adds memory, policy, and harness in AWS GovCloud (US-West)

Дата публикации: 07-08-2026 15:52:00

Today, Amazon Bedrock AgentCore introduces new capabilities in AWS GovCloud (US-West). AgentCore is the platform to build, connect, and optimize agents. With these capabilities, teams operating in regulated environments can build context-aware agents and take them from prototype to production faster, with the controls needed to scale across their organization. 
AgentCore memory gives agents short-term memory for immediate conversation context and long-term memory that extracts persistent insights and preferences across sessions. Agents deliver more intelligent, personalized experiences without teams needing to manage complex memory infrastructure.
Policy in AgentCore provides centralized, fine-grained controls for agent-tool interactions that operate outside agent code. Teams author policies in natural language that automatically convert to Cedar, the AWS open-source policy language. Policies attach them to an AgentCore gateway that evaluates each request before allowing or denying tool access. 
The managed harness lets developers declare an agent's model, tools, and instructions through configuration and run it in just a few API calls without writing orchestration code, while AgentCore handles the environment, compute, memory, identity, and observability. 
 
To learn more about AgentCore capabilities, visit the AgentCore product page. For a deeper walkthrough of AgentCore concepts and best practices, see the AgentCore Documentation to get started.

Основное содержимое страницы с новостью.

Today, Amazon Bedrock AgentCore introduces new capabilities in AWS GovCloud (US-West). AgentCore is the platform to build, connect, and optimize agents. With these capabilities, teams operating in regulated environments can build context-aware agents and take them from prototype to production faster, with the controls needed to scale across their organization. 

AgentCore memory gives agents short-term memory for immediate conversation context and long-term memory that extracts persistent insights and preferences across sessions. Agents deliver more intelligent, personalized experiences without teams needing to manage complex memory infrastructure.

Policy in AgentCore provides centralized, fine-grained controls for agent-tool interactions that operate outside agent code. Teams author policies in natural language that automatically convert to Cedar, the AWS open-source policy language. Policies attach them to an AgentCore gateway that evaluates each request before allowing or denying tool access. 

The managed harness lets developers declare an agent's model, tools, and instructions through configuration and run it in just a few API calls without writing orchestration code, while AgentCore handles the environment, compute, memory, identity, and observability. 
 
To learn more about AgentCore capabilities, visit the AgentCore product page. For a deeper walkthrough of AgentCore concepts and best practices, see the AgentCore Documentation to get started.

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Классификация: . Схожих патентов: 0. Схожих новостей: 10. Тональность: 0. Информативность: 8.21. Источник: aws.amazon.com.