The engineering library
Understand data boundaries, private inference, and the architecture behind a zero-egress deployment.
Private AI · Fundamentals
A practical starting point for deciding where AI should run, who should control it, and whether a private deployment fits your business.
Read the guide : What is private AI, and when does it make sense?Private AI · Fundamentals
Separate promises about data movement, data storage, and network transport before choosing an AI architecture.
Read the guide : Zero egress, zero retention, and private endpointsPrivate AI · Technical guide
Design the complete inference boundary, including retrieval, identity, logs, model preparation, and maintenance.
Read the guide : A reference architecture for zero-egress LLMsStart a conversation
Explain what you want to improve and which tools you use. I’ll ask a few questions and tell you whether I think I can help.
