Every Sandlake pod is single-tenant hardware, scoped to one enterprise's data from the start. It's the foundation for self-hosted inference and for fine-tuning or training a vertical model.
A pod is single-tenant GPU capacity, isolated at the network and storage layer, provisioned to one enterprise. It's the unit everything else runs on, no multi-tenant sharing, no other customer's workload anywhere near yours.
Any enterprise with proprietary data or internal know-how it can't expose to a public model provider.
Scoped to the workload and data footprint, not a fixed one-size package.
Fine-tune an open-weight model on your internal documents, code, and history, or train a vertical model from scratch for a specific domain. Either way, it happens entirely inside the pod. The data used to train never leaves, and it's never used to improve anyone else's model.
Fine-tune a coding assistant on your own codebase and incident history, or train a vertical model on domain-specific documents.
Your fine-tuning data is never used to train a shared or public model.
Query your model from inside your own environment. No prompts routed through a third-party API, no external logging, no exposure. Inference runs on the same dedicated pod the model was trained on, with no model provider in the loop.
Run internal Q&A over proprietary documents and data without it touching a public model provider.
Private endpoint, reachable only from inside your network or VPN.