Shaide

Distributed, multi-model LLM inference on Kubernetes you own - installed by a single command, all the way down to air-gapped clusters.

Standing up enterprise AI infrastructure today means assembling a long list of moving parts - an inference engine, a serving orchestrator, a gateway, a model registry, storage, observability, and that is only the beginning. Each one has to be chosen, configured and glued to the next, component by component, then again for every environment. shaide ships that whole stack as one installable platform.

The entire platform is managed as infrastructure as code . Every layer - the internal registry, the gateway, model serving and the application layer - is defined as a Pulumi project in this repository, so your AI infrastructure is versioned and reproducible.

And it stays inside your perimeter. shaide is built for organisations whose data cannot leave their infrastructure: regulated industries, defence, public sector, or anyone who simply will not send prompts to a third-party API. There is nothing phoning home and no dependency on a vendor's cloud - including fully air-gapped installations with no internet access at all.

Sovereign by design. Everything runs in your infrastructure. An internal OCI registry mirrors every container image and model weight, so a cluster can operate with no egress whatsoever.