AI creates needs your platform wasn’t built for — kagent enterprise bridges the gaps with cloud infrastructure for AI and agentic workloads.
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We’re building the future of agentic infrastructure with kagent, a collaborative open-source project backed by key contributors from the world's leading technology companies.
AI and agentic applications require a context-aware platform
Cloud-native platforms focus on identity and policy for users and workloads with platform RBAC. Agents and tools are considered black box workloads.
Agent-native platforms recognize agents and tools as first class workload types and treat agents acting on behalf of users as a distinct identity with the ability to set granular access policies for tools and agents.
Cloud-native platforms provide baseline metrics, logging, and tracing support for workloads, but lack context-awareness for interactions with agents, tools, and LLMs.
Agent-native platforms extend OpenTelemetry to provide context-specific access logging, usage metrics, and trace attributes for agents, tools, and LLMs. Context-aware instrumentation for agents and tools ensures that traces are propagated for end-to-end observability.
Cloud-native platforms leverage load balancers, gateways, and traffic proxies for HTTP, gRPC, and other Layer 7 protocols without understanding the body or context of a request.
Agent-native platforms support context-aware processing of Layer 8 protocols used for LLM consumption, MCP, and A2A with the ability to federate, multiplex, and process traffic with a deep understanding of the context of the request and response.
Cloud-native platforms view applications as opaque containers that are scheduled, deployed, and managed with no intelligence into the underlying workloads type or function.
Agent-native platforms provide a first class API to define, manage, and govern agents, tools, and models used for AI and agentic applications, supporting context-aware policy, routing, failover, and resiliency controls.
Cloud-native platforms are traditionally built for deterministic workloads that don’t require additional safeguards to interrupt or deeply observe contextual signals for monitoring application predictability and safety.
Agent-native platforms provide the governance controls required to confidently deploy and run probabilistic agents with built-in capabilities to support human-in-the-loop, human-on-the-loop, and real-time streaming of agent activity.
Establishing end-to-end security in a world of autonomous agents and insecure tool servers is one of the biggest challenges enterprises face in agentic architectures.
kagent enterprise integrates with your existing identity provider to establish end-to-end identity, policy, and on behalf of semantics to fully secure user, agent, and tool interactions.
When autonomous agents produce unexpected or incorrect outcomes, traditional telemetry leaves you blind to the root cause. Kagent enterprise extends observability beyond metrics and logs with deep, context-aware tracing of every agent, tool, and LLM interaction.
This end-to-end visibility enables precise debugging, auditable trails for compliance, and detailed consumption tracking for every interaction.
There will not be one agentic framework to rule them all, but there will be one platform on which you need to run them. Kagent enterprise provides a context-aware runtime for memory management, policy, registry, observability, and security for any agent framework (Langchain, Google ADK, A2A).
A centralized management plane and declarative API allow you to implement AgentOps across a distributed, heterogenous environment.
Agents require tools to do anything useful which has fueled a frenzy of MCP tool server development. With thousands of tool servers available in public registries and still more to build for internal services and APIs, connecting critical enterprise data, resources, and services to your agents is one of the biggest challenges in building production-ready agents.
Kagent enterprise supports a full lifecycle framework for building your own agents and integrating with existing agents, while bringing uniform security, observability, and secure sandboxing across all tools your agents access.
Kagent enterprise unifies security, observability, and lifecycle management into a single management plane to support AgentOps. With centralized visibility, an agent registry, global policy control, and human-in-the-loop safeguards, kagent enterprise provides organizations the control and confidence to scale agents and tools across any environment.
The future of AI and agentic infrastructure is being defined in open source communities. We are proud to not only participate in these communities, but to actively drive that innovation through our key projects within the CNCF and Linux Foundation.
Agent Connectivity Solved.
Bringing Agentic AI
to Cloud Native.
Accelerating MCP
for Cloud Native.
