Manage the AI you already have.

Kosmoy is an AI management platform for regulated enterprises — combining AI governance, AI observability, an AI gateway, and a Kubernetes-native AI agents sandbox in one platform. It manages every AI system in your company — public LLMs, private models, MCP servers, autonomous agents, custom apps, RAG systems, developer coding tools — across four layers: AI Inventory, AI Monitoring, AI Governance, and AI Action Control. Kosmoy runs in your own Kubernetes on Azure, AWS, GCP or on-prem.

Hyperscaler AI studios give you tools to build inside their cloud. Kosmoy is the management layer above them. You can register, monitor, govern and contain AI built on Foundry, Bedrock or anywhere else, from one platform. If you're multi-cloud or you're regulated, the management layer can't live inside one hyperscaler.

Kosmoy sits above your model providers and your cloud. The Gateway exposes one OpenAI-compatible API across every supported model, so swapping Claude for GPT for a private fine-tune is a configuration change in Kosmoy, not a code rewrite in every app. The platform deploys on Azure, AWS, GCP or on-prem and is portable between them. Your code keeps working when you change vendor. Your cost optimisation strategy stays yours. Your negotiating leverage with hyperscalers and model providers grows over time.

The Kosmoy AI Gateway is your LLM gateway, MCP gateway and agent gateway in one — the policy boundary between your apps and the AI they call. Every LLM, MCP and agent-to-agent call routes through it. Guardrails for toxic language, PII, prompt injection and policy compliance, cost tracking, RBAC and conversation logging are enforced at the gateway, not asked of each app.

An Action Capsule is Kosmoy's AI agents sandbox — a Kubernetes-native containment runtime around an agent, model or MCP server. The runtime is enclosed. The only egress is the Kosmoy Action Plane. Pre-flight authorisation, execution leases, just-in-time credentials, mediated actions and a kill switch are enforced at the runtime boundary.

No. Most enterprises start with the AI Gateway — Phase 1, governance over the models and chatbots they already have. Action Capsules are Phase 2, when autonomous agents start writing to systems of record. Same platform.

Every guardrail decision, every approval, every override is logged as an event with timestamp, actor, system and outcome. The audit trail covers risk management, technical documentation, record keeping, human oversight, quality management and transparency — the building blocks every emerging AI regulation requires.

In your own Kubernetes. No host changes, no node patches, no custom container runtime. Supported on Azure, AWS, GCP and on-prem.

Two ways. First, observability — every call is logged with model, app, team and cost, so you can see where spend is concentrated. Second, the LLM router automatically routes simple prompts to cheaper, smaller models. The price gap between a frontier model and a small model is often two orders of magnitude. Customers regularly cut spend 90% on routable workloads.

Yes. Public LLMs, private LLMs, small fine-tuned language models. The platform is model-agnostic.