t cht lk rapid development and change, and it delivers on the event-driven architecture that allows for managing rate mismatch, supporting different applications with messaging patterns, and delivering efficiency needed to scale horizontally and vertically. framework underpinning agent mesh allows organizations to easily update, replace or add new AI models and data sources without disrupting existing systems. This is especially crucial for staying current with AI advancements.
t cht lk rapid development and change, and it delivers on the event-driven architecture that allows for managing rate mismatch, supporting different applications with messaging patterns, and delivering efficiency needed to scale horizontally and vertically. framework underpinning agent mesh allows organizations to easily update, replace or add new AI models and data sources without disrupting existing systems. This is especially crucial for staying current with AI advancements.
When you apply the architectural pattern enabled by the event mesh across agentic AI use cases, you essentially create a flexible, real-time data distribution network that enables various AI models to access and react to relevant data streams instantly.
And now meet the agent mesh
While an event mesh enables real-time data flow and dynamic routing across the enterprise, an agent mesh takes this further by introducing intelligent agents that can autonomously reason about, and act on, this information flow.
The future of AI agents will include an agent mesh
Agentic AI is a sea change in the use of AI, going beyond simple LLM applications to create autonomous systems capable of never-before-seen levels of reasoning and adaptation. To realize its full potential to dynamically manage inventory levels in a warehouse or reconfigure supply chains on the fly means addressing its need for real-time, contextual information flow.
This is where the agent mesh will become the key to maximizing the value of AI agents in these dynamic business environments. p
An agent mesh is a framework that allows you to build a network of AI agents overseen and controlled by a dynamic orchestration layer, allowing complex tasks to use multiple agents and bring their results together in a data management system. Agent mesh gateways allow access to this system for many different use cases, each with its own type of input interface and authorizations.
Essentially, organizations can enable truly autonomous Agentic AI systems that can manage requests to deliver the best results based on unstructured inputs, such as chats.
A flexible, composable AI framework means organizations can pace themselves...
Best of all, an agent mesh is not intrusive to an organization’ s existing application stack and Agentic AI framework. With its‘ plug-and-play’ style approach, organizations can start small with one or two use cases and then over time evolve the agent mesh by adding agents to increase its capabilities, as well as new agent mesh gateways to add further use cases and interfaces to the system.
... then evolve in lockstep with business growth
Then, with orchestration and built-in access control of all agents and actions in the system, one framework can be used and re-used for many use cases – be it a new order, a new support ticket or even a question from a chatbot – each providing different interfaces and access control that is governed by enterprisegrade security.
In a landscape where AI technologies are rapidly evolving, the decoupled nature of an event-driven
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