Amazon Bedrock AgentCore: The Foundation for Enterprise AI Agents

Introduction

Artificial Intelligence (AI) has progressed to the point where it can mimic human interactions and behaviours to perform a wide variety of activities and tasks. Advances in Large Language Models (LLMs) enable various companies to embed AI in their products. However, using LLMs at scale requires organisations to build secure, flexible computing infrastructure, which is where Amazon Bedrock AgentCore comes in. AgentCore provides a fully managed service for businesses to build and deploy AI agents at scale. The service, offered by Amazon Web Services (AWS), helps businesses build AI agents quickly.

What Does AgentCore Solve For You?

AI solutions are often prototyped quickly. However, there are a number of challenges organisations face when they seek to commercially deploy AI solutions at scale, including security, integration with enterprise systems, governance and management, and observability.

Before the release of AgentCore, integrating these capabilities with AI agents required significant software engineering effort. With AgentCore, developers can focus on implementing business logics and rules while AgentCore manages the remaining tasks.

 What Does AgentCore Provide?

AgentCore provides several services, including an AI agent runtime that supports concurrent requests and scales automatically with workload.

AgentCore Memory

Memory enables agents to retain information about the user, their preferences, and other details that enhance the user experience.

AgentCore Gateway

The Gateway provides agents with access to enterprise services and applications by connecting to enterprise resources and other services.

AgentCore Identity

Identity integrates with enterprise ID and access management (IDAM) systems and other enterprise security solutions and controls, and controls access and secures agent activities on users’ behalf.

AgentCore Code Interpreter

Agents can run different programming languages (such as Python, JavaScript, and TypeScript) in a secure environment to manipulate and analyse data.

AgentCore Browser

Through an agent’s control of a browser, a user experience can be designed to automate tasks that users previously performed, such as filling out web forms and using applications.

AgentCore Policy

The Policy defines and validates the limits and constraints on activities performed by agents and helps organisations operate in compliance with applicable rules and regulations.

AgentCore Observability

The Observability element enables personnel to collect data on and analyse agents’ activities to optimise their performance.

Enterprise Use Cases

Organizations can use AgentCore across various business domains:

• Customer Support: Automating responses, ticket creation, and issue resolution.
• Knowledge Management: Building intelligent assistants that retrieve organizational knowledge and documentation.
• Compliance Automation: Monitoring regulatory changes and generating compliance reports.
• Content Generation: Orchestrating multiple agents for research, creation, validation, and publishing workflows.
• Business Process Automation: Connecting agents to CRM, ERP, and operational platforms for end-to-end workflow automation.

Benefits of AgentCore

Enterprises want to accelerate their AI journey, but building and managing AI applications at scale is a major challenge. We describe how our managed AI services address these challenges:

• Reduce Infrastructure Management Effort
  Enterprises no longer need to build and manage custom AI application development or runtime infrastructures. Amazon Web Services (AWS) manages the underlying infrastructure, allowing enterprises to focus on AI business outcomes.
• Faster time to Market
  AgentCore services reduce the time and effort required to develop AI applications, and hence, help enterprises quickly move their AI application development from POC to production.
• Scale Automatically
  AgentCore provide a serverless, dynamically scalable runtime environment. Therefore, enterprises do not need to manually manage or provision server resources to scale their AI applications.
• Improve Security and Governance
  AgentCore offers enterprises control over the security of their AI applications. For instance, identity management, session isolation and authentication help enterprises secure their applications.
• Persistent Agent Memory
  AgentCore allows enterprises to provide persistent memory to their agents, enabling them to remember user preferences and other context from previous interactions. Long-term memory helps enterprises to create applications with enhanced user engagement and individualised interactions.
• Simplify Enterprise Integrations
  For enterprise integrations, AgentCore provides an enterprise gateway for connecting to databases and APIs, including AWS and 3rd-party services. Using AgentCore, businesses can have AI agents help them perform a variety of business tasks.
• Enhance Monitoring and Debugging
  Tracing, telemetry, logging, and performance insights are provided by AgentCore Observability to help teams understand agent activity, monitor tool usage, resolve issues, and continuously improve agent performance.
• Support Multiple Agent Frameworks and Models
  AgentCore provides a generic agent SDK that is framework agnostic. AgentCore out of the box supports Google AI Development Kit (ADK) and OpenAI Agents SDK. Similarly, AgentCore supports numerous agent frameworks and models. Because of AgentCore’s generic nature, businesses using it can avoid vendor lock-in.

Conclusion

An important development in enterprise AI is Amazon Bedrock AgentCore. AgentCore streamlines the process from AI prototype to production by integrating runtime execution, memory, identity, governance, integrations, and observability into a fully controlled platform. While AWS handles the infrastructure, scalability, and operational complexity, organisations can focus on developing intelligent business solutions. AgentCore provides a solid foundation for creating safe, dependable, and scalable enterprise AI agents as agentic AI evolves.