One private AI stack, from bare metal GPUs to deployed engineers
Each part of the PrivateMind stack is useful on its own. Together they give a financial firm everything it needs to run AI privately, without stitching providers together or running a data centre.
- 01
GPU & Infrastructure
Bare metal access to NVIDIA B300, B200, H200, H100 and RTX PRO 6000 GPUs in dedicated AI data centre space, with managed networking, storage and 24/7 operations.
- From part of a node to whole pods of GPUs
- Up to 800G Ethernet, isolated by default
- Block, object and high-performance storage with VAST and Everpure
- 02
Control Plane
Everything your ML engineers need to train, register and serve models on dedicated GPUs we run for you, without having to become infrastructure specialists first.
- GPU allocation down to MIG slices, with drivers built in
- Training with Ray on Kubernetes, tracked in MLflow
- Custom inference endpoints for the models you train and host
- 03
Workspaces
Agentic coding environments on GPUs and CPUs reserved for your firm, with VS Code, a terminal, OpenCode and Jupyter ready to go. Use them in the browser or from your own machine through the SDK and CLI.
- Coding agents run in a controlled environment on our GPUs
- PrivateMind API keys are minted automatically, so setup takes minutes
- Quant templates with market data from AtlasFeed already connected
- 04
Platform
Private LLM inference through chat and an OpenAI-compatible API, with cost-effective open-weight models alongside Claude, OpenAI and Amazon Bedrock, and every client kept in its own database.
- Hybrid routing across open-weight and frontier models, in chat and the API
- Model aliases that route around an unavailable model
- Separate databases by client
- 05
AI Solutions
Our AI engineers work with your people to find the workflows where AI saves the most time or removes the most risk, build the solution with them and keep improving it.
- Deployed AI engineers embedded in your teams
- Workshops for leadership, analysts and engineers
- A clear path from first use case to production: discover, deploy, advance
What is the PrivateMind stack?
Five products in one private stack for financial firms: bare metal GPU and infrastructure, an MLOps control plane, secure workspaces, private LLM inference, and deployed AI engineers. Each part is useful on its own, and together they give a financial firm everything it needs to run AI privately.
Can we use one part of the stack on its own?
Yes. Each part of the PrivateMind stack is useful on its own, so you can start with a single layer, such as GPU infrastructure or the inference platform, without stitching providers together.
Do we need to run the data centre ourselves?
No. The infrastructure layer gives you bare metal access to NVIDIA GPUs in dedicated AI data centre space, with managed networking, storage and 24/7 operations, so your teams can focus on the work.
Start free today, or request a demo of private AI for your firm
Create an account to use chat and the API straight away, or request a demo to see dedicated capacity, workspaces and engineers for your team.