Private AI implementation
Private AI means the model runs where your data stays: on your hardware or private cloud, with no third-party AI service in the loop. We implement assistants and pipelines on open models, the same approach we run every week to produce this newsletter.
What you get
Scoped per project
- Open-model selection and sizing for your hardware or private cloud
- Deployment on your infrastructure, with no third-party AI service in the loop
- The same approach we run every week for this newsletter
- Hooks for guardrails and audit logging from day one
When this fits
- Your data cannot be sent to a third-party AI service.
- You want to know what hardware an open model needs before you buy it.
- You need logging and guardrail hooks built in, not added later.
How it works
Size it
We match open models to the task and to the hardware or private cloud you have.
Deploy it where your data is
The assistant or pipeline is installed on your infrastructure and tested without sending your data out.
Hand over
You keep the code in your repository, with the guardrail and audit-logging hooks in place.
Common questions
What is private AI?
Can you build and test without our data leaving the building?
Do we still need guardrails if the model is private?
What does it cost?
Related
Have a system to build, secure or document?
Tell us what it is and we’ll get back to you within 48 hours.
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