Managed Private AI Private AI, built around your data and your daily work.
Put document search, drafting and approved workflows on infrastructure under your control. Z7 assesses the workload, designs the data boundary, deploys supported models and scopes the support your team needs.
- Defined data boundary
- Supported local models
- Access and evaluation plan
- Scoped managed support
What to decide before you begin
A useful engagement starts with a specific outcome and clear responsibilities.
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Start with one real workflow
Bring a representative task, a data owner and a small approved sample. The assessment produces a deployment design, an access map, an evaluation plan and an operating-cost model.
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Define the whole boundary
Record where prompts, retrieved passages, embeddings, outputs, logs and backups go. External connectors, remote support and optional cloud inference require their own approved paths.
Use the readiness guide -
Approve evidence before expansion
Test source accuracy, denied access, unsupported questions and peak concurrent use. Agree on failure limits, human review, rollback and support responsibilities before adding users.
A private AI appliance, run by Z7
Model serving, retrieval, access controls and support are designed around your approved environment.
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Open-weight and fine-tuned models
Reasoning, chat, document analysis, coding, and domain-tuned guard models, running locally.
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Your data stays put
Local inference keeps prompts and model processing within the chosen boundary. Review connector, telemetry, backup and support paths as part of the design.
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Agentic workflows behind your firewall
Retrieval over your document stores, tool use against your internal systems, and automation of real work.
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Governance and security layer
Data classification, prompt-injection defense, output filtering, and audit logging, with your existing controls in front of it.
Three deployment tiers
Every tier runs on premises, answers from your own documents, and puts a guard layer in front of the model. A short assessment sizes the workload first; its output is a deployment design and a real cost model.
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Template
Least customization
Z7's base model with retrieval over your own documents, deployed on premises with minimal customization.
- On-premises deployment
- Retrieval over your documents
- Guard layer in front of the model
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Tailored
Light customization
Everything in Template, plus a persona or light fine-tune and integrations with your workflows and systems.
- Everything in Template
- Persona or light fine-tune
- Workflow and system integrations
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Custom
Full customization
A dedicated fine-tuned model behind a custom dashboard your users sign in to, branded and configured for your workflow.
- Dedicated fine-tuned model
- Custom dashboard for your users
- Branding and configuration
What Z7 delivers
One accountable team from sizing the workload to running it every day.
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Assess
A short engagement sizes the workload: use cases, users, models, throughput, and hardware. The output is a deployment design and a real cost model.
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Deploy
We stand up the hardware and software, select and tune the models, and design the network that keeps everything inside your perimeter.
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Operate
Managed operations on a monthly retainer: 24/7 monitoring, model version management, prompt and retrieval tuning, capacity planning, governance audits, and support with response targets published in our SLA.
Built for data that cannot leave
For any organization where the data simply cannot leave, from small business to enterprise.
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Healthcare
Patient records under HIPAA.
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Legal firms
Client work under privilege.
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Education
Records protected by FERPA.
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Utilities and water authorities
OT and IT kept segmented.
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Government
Data residency mandates.
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Financial services
Client data that cannot leave.
- Z7 runs its own model serving and training
- Z7 trains its own guard and domain models
- Vendor-neutral recommendations
- In business since 2012
- 24/7 SOC, NOC, and help desk
- ISO 9001, 27001, 20000, 22301 aligned
- Microsoft CSP
- Google Partner
Private AI questions
Decisions, scope and operating responsibilities.
What hardware runs Private AI?
Z7 supplies on-premises hardware sized to your workload, including Apple Mac mini and Mac Studio class systems. The assessment defines the configuration and operating responsibilities.
Which models can we use?
Open-weight and fine-tuned models are selected for the use case, deployment rights and hardware. The proposal records the supported models and operating scope.
How long does deployment take?
The assessment establishes your integration needs, acceptance criteria and delivery timetable. We scope the timeline before committing to deployment.
Can Private AI support work involving PHI?
We review the data flow and required safeguards with you. A business associate agreement is required where the engagement places PHI in scope; the deployment does not remove your compliance obligations.
How is Private AI priced?
A per-user lease plus maintenance is scoped on a call. Hardware, integrations, support and any additional work are defined in the proposal.
Does private AI mean no data can ever leave the network?
Local inference can keep model processing inside the chosen boundary. That result depends on configuration: connectors, telemetry, backups, remote support and any cloud fallback must be reviewed and controlled. Z7 documents those paths in the deployment design.
What drives the operating cost?
Hardware or lease, capacity, storage, backup, power, licensing, integration maintenance, evaluation and support all matter. Local inference can reduce usage-based model charges, but it does not make operations costless. We size costs against the workload and agreed service scope.
Can we evaluate before committing to a larger rollout?
Yes. Scope a bounded pilot with approved data, a named business owner and written acceptance criteria. Compare useful completed work, review effort and total operating cost before expanding.
Define your first Private AI deployment
Bring one workflow and its data requirements. We will scope the design, evaluation and operating responsibilities.