Sold by: LorinCloud
The rapid evolution of Large Language Models and Agentic AI has created demand for production-grade hosting environments where organizations can reliably run and scale agent-based applications in the cloud.
While many companies can prototype early-phase agentic applications, far fewer can design and operate agent-runtime platforms that are reliable, secure, scalable, operationally efficient, performance-efficient, and cost-efficient.
The Agentic AI Landing Zone of LorinCloud addresses this gap by providing a custom AWS-based foundation for hosting and running AI agents. It abstracts the complexity of infrastructure design, security, observability, deployment, and runtime operations, enabling customers to focus on business value instead of platform engineering.
By reducing complexity and accelerating experimentation, the solution helps customers create, productize, and scale agents faster, resulting in shorter delivery cycles, faster time to value, and efficient AI development.
Overview
The solution provides a robust, resilient, reliable, secure, operationally efficient, and performance-efficient cloud infrastructure environment for hosting and running Agentic AI applications.
It consists of a mature AWS cloud infrastructure layer, an agent runtime environment, short- and long-term memory modules, configurable vector database modules, monitoring and observability components, MCP integration capabilities, security components, and LLM integration endpoints.
The solution leverages modern AWS Agentic AI services and resources, in particular Amazon Bedrock AgentCore, Bedrock-hosted Large Language Models, and AWS-hosted vector database options. It makes use of the core capabilities of Amazon Bedrock AgentCore to support the reliable and secure operation of agent-based applications. AgentCore Runtime is used for hosting and running agents. AgentCore Observability enables near real-time monitoring, tracing, debugging, and application-level visibility. AgentCore Memory supports multi-tier memory strategies, including short-term and long-term memory modules with customizable memory approaches. AgentCore Identity is incorporated to provide agent-based authentication and authorization capabilities, while AgentCore Gateway is used to enable secure integrations with tools, services, and MCP-compatible components. AgentCore policy controls can also be applied as logical security boundaries for governing agent behavior and access.
The solution is delivered as a custom implementation through LorinCloud’s professional services offering. It is highly customizable and can be tailored to specific customer requirements, architectural constraints, security needs, integration patterns, and operational expectations.
The solution can also be integrated with other enterprise systems and cloud services to establish a stable Agentic AI environment for prototypes, MVPs, and production-grade systems.
With LorinCloud’s customized Agentic AI Landing Zone, engineering teams can focus on developing key value-creating Agentic AI applications, while LorinCloud provides the secure, scalable, and production-ready infrastructure foundation required to host, operate, monitor, and evolve those applications on AWS.
Highlights
- Production-ready Agentic AI foundation on AWS for securely hosting, running, and scaling AI agents across prototypes, MVPs, and enterprise-grade systems.
- Integrated runtime, memory, observability, security, vector database, MCP, and LLM capabilities built around Amazon Bedrock AgentCore and AWS-native services.
- Custom professional services implementation that lets engineering teams focus on value-creating agent applications while LorinCloud delivers the cloud infrastructure foundation.
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