About CaseDesk

We built the platform that makes AI adoption practical.

Teams need a clear use case and a trusted way to govern it. CaseDesk turns valuable AI work into a private platform connected to infrastructure the organisation controls.

The problem we solve

Most teams do not need another model catalogue. They need a useful, safe way to apply AI to coding, internal questions, document work, or automation without creating a new platform project.

Operating a runtime still requires a provider account, capacity, and accountable owners. CaseDesk keeps that ownership clear while reducing the platform work around compatible APIs, policy, routing, and observability.

CaseDesk connects the endpoint your organisation or provider controls for the work you choose, in the region you need, using the OpenAI, Anthropic, and Gemini-compatible interfaces your tools already speak.

What we believe

Privacy by architecture, not policy

Your organisation chooses the runtime region and data boundary. CaseDesk records and verifies the connected endpoint rather than taking ownership of the runtime.

No lock-in

CaseDesk uses compatible APIs and supports customer-controlled vLLM endpoints. You can change your approved runtime without replacing every application integration.

Simplicity over features

One governed API surface for supported tools. CaseDesk keeps policy, routing, connection health, and operational evidence together without taking over capacity operations.

Honest pricing

Your provider bills runtime capacity directly. CaseDesk charges separately for the platform services you select, with prepaid credit and clear connection charges.

Your model and infrastructure stay under your control.

CaseDesk provides the control plane, compatible API, policy controls, and operations layer. Your organisation selects and pays for its own cloud, provider, Kubernetes cluster, or GPU VM. CaseDesk does not take ownership of your GPU capacity.

What you can take with you is the integration boundary. CaseDesk uses compatible API formats and does not require an application-specific SDK. Your runtime choice remains explicit, whether you use an approved vLLM endpoint or another supported provider endpoint.

You can connect AWS, Azure, an on-premise server, a Kubernetes cluster, or a GPU VM, subject to verification. The compatible API integration can remain stable while you change an approved runtime.

We think this is the honest way to sell AI operations: you choose CaseDesk for the control plane and support, not because your infrastructure is locked to us.

Who we are built for

Get in touch

We are a small, focused team. If you have a question that the docs do not answer, you will reach a human who built the product.

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