Latest news with #AgentCore
Forbes
18-07-2025
- Business
- Forbes
AWS Targets Enterprise AI Agent Production Gap With AgentCore Platform
Agents Amazon Web Services has introduced AgentCore, a managed platform specifically designed to bridge the challenging transition from AI agent prototypes to production-ready enterprise applications. The platform addresses infrastructure complexities that frequently stall enterprise AI initiatives, offering seven integrated services that handle runtime management, memory systems, and security controls. The announcement signals AWS's recognition of a critical market need. While organizations increasingly experiment with AI agents, many struggle to deploy them at scale due to infrastructure limitations, security concerns, and operational complexity. AgentCore positions AWS to capture enterprise spending as companies move beyond pilot projects toward production deployment. A Look at the Platform Components AgentCore consists of seven core services that work independently or together. The runtime component provides serverless execution environments with complete session isolation and support for workloads lasting up to eight hours—currently the longest in the industry. This addresses a fundamental challenge where traditional serverless platforms struggle with the unpredictable execution patterns of AI agents. The memory service manages both short-term conversational context and long-term knowledge retention across sessions. Unlike basic chatbot implementations, AgentCore Memory maintains persistent learning capabilities, enabling agents to improve performance over time. This persistent memory capability differentiates the platform from simpler AI assistant tools that reset context between interactions. Security integration happens through AgentCore Identity, which connects with existing enterprise identity providers including Amazon Cognito, Microsoft Entra ID, and Okta. The service enables agents to access internal systems while maintaining proper authentication and authorization controls. This enterprise-grade security model addresses compliance requirements that often delay AI agent deployments. Additional services include AgentCore Gateway for API integration, a browser tool for web automation, a code interpreter for secure code execution, and observability features powered by Amazon CloudWatch. The modular design allows organizations to adopt components incrementally rather than requiring complete platform migration. Competitive Landscape and Market Positioning AgentCore enters a competitive enterprise AI agent market currently dominated by platform-specific solutions. Google's Vertex AI Agent Builder offers similar capabilities but requires organizations to operate within Google Cloud's ecosystem. Microsoft's Azure AI Foundry Agent Services provide deep integration with Microsoft products but lack the framework-agnostic approach that AgentCore emphasizes. The platform's support for open-source frameworks including Strands Agents, LangChain, CrewAI, and LlamaIndex differentiates it from vendor-locked alternatives. Organizations can use any foundation model, including those hosted outside Amazon Bedrock, providing flexibility that appeals to enterprises with diverse AI strategies. This approach contrasts with Google's Vertex AI Agent Builder, which primarily integrates with Google's model ecosystem. AWS has also introduced a marketplace for pre-built AI agents and tools, creating a distribution channel that could accelerate enterprise adoption. The marketplace approach mirrors successful software distribution models and may provide AWS with additional revenue streams beyond core platform services. Implementation Challenges and Enterprise Considerations Despite its comprehensive feature set, AgentCore faces implementation hurdles common to enterprise AI deployments. The platform requires organizations to restructure workflows around agent-based automation, which can encounter resistance from teams accustomed to traditional software development practices. Technical skills gaps remain a significant barrier, with many organizations lacking the expertise to effectively deploy and manage AI agents at scale. Security concerns persist despite AgentCore's built-in controls. AI agents can accumulate system permissions that create expanded attack surfaces, and their autonomous decision-making capabilities introduce unpredictable behavior patterns that conventional security tools struggle to monitor. Organizations must implement additional governance frameworks to ensure agents operate within acceptable risk parameters. The platform's consumption-based pricing model, while offering cost flexibility, can create budget uncertainty for organizations with variable AI workloads. Runtime costs depend on CPU utilization and memory consumption, making it difficult to predict expenses for complex agent deployments. This pricing structure may favor organizations with predictable agent usage patterns over those with sporadic or experimental implementations. Strategic Implications for Enterprises AgentCore represents AWS' strategic response to enterprise AI maturation. As organizations move beyond generative AI experiments toward production automation, managed agent platforms become critical infrastructure. The platform's emphasis on security, scalability, and observability addresses key enterprise requirements that have limited AI agent adoption. However, success depends on AWS's ability to reduce operational complexity while maintaining enterprise security standards. Organizations that successfully deploy AI agents report significant productivity gains and cost reductions, but implementation requires careful planning and skilled technical teams. AgentCore's effectiveness will ultimately be measured by its ability to democratize AI agent deployment beyond technically sophisticated early adopters implementing proof of concepts. AgentCore's framework-agnostic approach positions AWS to capture enterprise spending regardless of specific AI implementation choices. This strategy may prove more sustainable than vendor-locked alternatives as the AI agent market matures and organizations seek to avoid technology dependencies that could limit future flexibility.
Techday NZ
18-07-2025
- Business
- Techday NZ
AWS unveils Bedrock AgentCore & boosts generative AI with $100 million
Amazon Web Services (AWS) has announced new offerings to advance the use and management of AI agents, including the introduction of Amazon Bedrock AgentCore, new Marketplace solutions, and additional investment in generative AI development. Amazon Bedrock AgentCore At the centre of the update is Amazon Bedrock AgentCore, described as a comprehensive suite of services for building, deploying, and operating AI agents securely at scale. AWS states that the aim is to help organisations transition from AI agent experimentation to robust enterprise deployment, ensuring compliance with security, reliability, and governance standards. The new AgentCore platform incorporates several components. AgentCore Runtime provides secure and dynamic support for interactive and asynchronous workloads, allowing agents to operate up to eight hours, which AWS claims is the longest in the industry. Session isolation and compatibility with any framework are also highlighted features. AgentCore Memory supports both short-term and long-term memory functions for agents, aimed at enabling more context-aware responses with high accuracy. AgentCore Identity addresses authentication, allowing AI agents to securely access a range of tools and services while integrating with existing identity solutions like Amazon Cognito, Microsoft Entra ID, and Okta. AgentCore Gateway gives AI agents a means to securely discover and utilise APIs, Lambda functions, and other resources, transforming them into agent-compatible tools. Meanwhile, AgentCore Code Interpreter enables secure execution of code within sandboxed environments, offering customisability around security and computational needs. To facilitate agent interaction on the web, the AgentCore Browser Tool allows agents to navigate websites and complete forms at scale via a secure, model-agnostic cloud browser. For operational visibility, AgentCore Observability - powered by Amazon CloudWatch - provides dashboards and telemetry covering 81 metrics, supporting integration with established observability frameworks. Early adopters, including Itaú Unibanco, Innovaccer, Boomi, Epsilon, and Box, are already utilising AgentCore in developing their AI agent solutions. "It's a tectonic change in a few dimensions," said Swami Sivasubramanian, AWS VP for Agentic AI. "It upends the way software is built. It also introduces a host of new challenges to deploying and operating it, and potentially most impactfully, it changes how software interacts with the world - and how we interact with software." Marketplace expansion AWS has launched a new AI Agents and Tools category in the AWS Marketplace. This addition is intended to simplify the process for organisations seeking commercial AI agent solutions, enabling customers to discover, buy, deploy, and manage offerings from various providers through a consolidated interface. According to AWS, the Marketplace enhancements are designed to accelerate adoption by providing customers with streamlined access to professional services and pre-built tools required to build, maintain, and scale agentic systems. Generative AI investment AWS has pledged an additional $100 million to the AWS Generative AI Innovation Centre, bringing further resources to support the global push towards agentic AI systems. The centre's teams collaborate with customers and partners, focusing on productivity improvements and customer experience transformation through AI. Several AWS customers have reported practical outcomes from working with these AI offerings. Warner Bros. Discovery Sports Europe has developed an AI-driven solution that assists cycling commentators in rapid fact-finding. The solution utilises Amazon Bedrock, Anthropic's Claude 3.5, and over 100 AWS services. BMW has also built an AI system on AWS to streamline diagnostics for over 23 million connected vehicles. Other companies cited include Syngenta and AstraZeneca, both reporting that agentic AI has contributed to changes in their operational models. The global team supporting the Generative AI Innovation Centre comprises AI scientists, strategists, and engineers who work directly with customers to address technological challenges, especially those related to enterprise implementation and scale.
Techday NZ
17-07-2025
- Business
- Techday NZ
AWS unveils AgentCore suite & invests USD $100 million in AI agents
AWS has introduced new tools and investments aimed at supporting organisations to build and deploy AI agents securely and at scale. Central to these developments is Amazon Bedrock AgentCore, a suite of seven core services that enable companies to develop, deploy and manage enterprise-grade AI agents. The announcement also includes an expanded AWS Marketplace for AI tools and agents, and an investment of USD $100 million in the AWS Generative AI Innovation Centre to accelerate agentic AI development. AgentCore features Amazon Bedrock AgentCore provides a framework-agnostic set of services designed to support the transition from AI experimentation to enterprise deployment. The suite covers runtime, memory, identity, tool integration, code interpretation, web browsing, and observability, aiming to address key technical and governance needs for production-ready AI agents. Swami Sivasubramanian, AWS Vice President for Agentic AI, outlined the company's strategy. He emphasised that AI agents - autonomous software systems that reason, plan, and adapt - could significantly accelerate productivity and outcomes in multiple industries. He said: "It's a tectonic change in a few dimensions. It upends the way software is built. It also introduces a host of new challenges to deploying and operating it, and potentially most impactfully, it changes how software interacts with the world - and how we interact with software." AgentCore's seven core services are designed to meet different operational aspects of running secure and scalable AI agents: AgentCore Runtime supports both low-latency interactive experiences and complex asynchronous workloads for up to eight hours, and provides session isolation in a framework-agnostic manner. supports both low-latency interactive experiences and complex asynchronous workloads for up to eight hours, and provides session isolation in a framework-agnostic manner. AgentCore Memory offers long-term and short-term memory functionalities for agents to maintain context, aiming for high accuracy across memory types. offers long-term and short-term memory functionalities for agents to maintain context, aiming for high accuracy across memory types. AgentCore Identity integrates seamlessly with existing identity providers, such as Amazon Cognito, Microsoft Entra ID, and Okta, to secure and manage agent authentication. integrates seamlessly with existing identity providers, such as Amazon Cognito, Microsoft Entra ID, and Okta, to secure and manage agent authentication. AgentCore Gateway enables secure access to a variety of digital tools, allowing easy transformation of APIs, Lambda functions, and existing services into agent-compatible resources. enables secure access to a variety of digital tools, allowing easy transformation of APIs, Lambda functions, and existing services into agent-compatible resources. AgentCore Code Interpreter allows agents to execute code safely in sandboxed environments and can be tailored to meet varying security and instance requirements. allows agents to execute code safely in sandboxed environments and can be tailored to meet varying security and instance requirements. AgentCore Browser Tool gives AI agents secure web access for automated online tasks, suitable for operations such as web form completion or navigating websites. gives AI agents secure web access for automated online tasks, suitable for operations such as web form completion or navigating websites. AgentCore Observability leverages Amazon CloudWatch for real-time monitoring, dashboards, and telemetry, while integrating with customers' observability systems. Customer organisations including Itaú Unibanco, Innovaccer, Boomi, Epsilon, and Box have begun utilising AgentCore as they seek to embed AI agents into their operations. Secure & production-ready According to Sivasubramanian, these services are aimed at helping customers as models and use cases evolve, allowing businesses to maintain secure deployment while scaling their AI capabilities. He highlighted the need for systems that can adapt as requirements change and said: "Building systems that can act autonomously across digital boundaries, while maintaining the security, reliability, and governance standards required for enterprise deployment, is a critical challenge. AgentCore helps developers bridge the critical gap between proof of concept and production for AI agents. It delivers a set of composable solutions that allows organizations to move agents from prototypes to applications that can scale to millions of end-users." Marketplace expansion AWS is expanding its Marketplace to introduce a new category, AI Agents and Tools. This aims to help enterprises discover, purchase, and deploy AI agent solutions from a selection of providers. The intention is to streamline the process for organisations seeking to adopt AI agents, providing access to solutions and professional services for building, maintaining, and deploying agents at scale. Sivasubramanian discussed this expansion during his remarks at the AWS Summit in New York, saying customers have access to a one-stop shop to accelerate the development of their AI initiatives. Customers leveraging these Marketplace solutions are expected to benefit from streamlined integration and delivery, with the support of specialist service providers. Investment AWS also announced a further USD $100 million for the AWS Generative AI Innovation Centre to support the development and deployment of agentic AI. This investment is designed to help businesses build and scale AI agents tailored to specific industry needs, supporting customers at various stages of their AI adoption journeys. Additional enhancements to Amazon Nova were announced, offering customers improved customisation for building specific AI capabilities with higher accuracy and flexibility. With these latest announcements, AWS aims to provide a more robust platform and ecosystem for organisations interested in deploying secure, scalable AI agents in production environments.
