Powering AI innovation in Kubernetes

Solo provides the agentic infrastructure and tooling you need to build and deliver your AI strategy at scale with security, observability, and resiliency as first principles

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Organizations building with Solo.io

The demand from AI usage is scaling. Your team isn’t.

AI introduces a new dimension of scale and complexity, with required work growing far faster than platform team capacity.

Without new tools to bridge this delivery gap, your entire AI strategy is at risk.

Introducing Kagent

Kagent is a powerful agentic AI framework and toolkit, purpose-built for Kubernetes. Engineered from the ground up based on platform best practices, Kagent makes it easy for you to build and manage agentic AI applications with the same confidence and control you apply to your cloud-native applications.

Agentic infrastructure powered by leading cloud-native technologies

Unlock the power of Kubernetes-native AI

Build

Our innovative agent development framework

Accelerate development with out-of-the-box agents for common SRE and platform engineering tasks, which can also serve as templates.
Easily create custom intelligent agents tailored to your specific operational workflows and business logic.
Develop using familiar paradigms without deep Python or ML expertise.
Define agent behaviors, tool integrations, and data sources through a declarative approach that aligns with your existing Kubernetes practices.

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Inference

Secure, scale, and optimize model serving and inferencing

Optimized routing to LLMs based on model capability, capacity, and underlying infrastructure to drive cost efficiency and response quality.  
Support multi-tenant access to pools of fine-tuned LLMs to support multiple use cases, applications, and consumers of inference pools on shared infrastructure.  
Comprehensive security and observability controls for LLM access supporting fine-grained authorization/authentication, model telemetry, and auditing.

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Run

Security, observability, and governance for AI and agentic infrastructure

Take control of LLM access from applications and agents with security guardrails, access control, consumption reporting, and semantic caching.  
AI-native protocol support for MCP and A2A to support agent-to-agent and agent-to-tool interactions with a federated agent gateway and centralized secure catalog for agents and tools.
Full support for Gateway API Inference Extensions to secure, scale and optimize inference within Kubernetes.

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