Some organizations cannot send their data to a public AI cloud. Not would rather not. Cannot. The public AI question has had two bad answers: ship sensitive data to someone else’s cloud, or sit out the AI era. Managed Private AI is the third answer: the same modern models, on hardware you own, inside your perimeter, with your data never leaving the building.
Healthcare under HIPAA. Legal firms under privilege. Education holding FERPA-protected records. Utilities and water authorities with OT/IT segmentation. Government with residency mandates. Financial services and any organization where the data simply cannot leave, from SMB to enterprise.
A short engagement to size the workload: use cases, users, models, throughput, and hardware. Output: a deployment design and a real cost model.
We spec and stand up the hardware and software: local model serving, retrieval pipelines, agent runtime, identity integration, and the network design that keeps it inside your perimeter.
We pick the right models and, where it helps, fine-tune on your domain. Z7 trains its own models on its own infrastructure, including domain guard models for regulated settings.
Data classification, prompt-injection defense, output filtering, audit logging, usage policy, and regulator-ready documentation, with your existing controls in front of it.
A monthly retainer: 24/7 monitoring, model version management, prompt and retrieval tuning, capacity planning, governance audits, and SLA-backed support.
Your AI strategy should not require it to. Let us show you what private AI looks like done right.
