Private AI that stays inside your company

Move fast on AI without losing control: clear boundaries, owned systems, and a path you can reverse if needed.

Direct work. Limited availability. If this is relevant, email me.

Email: claudius@claudio.one(short note is enough)

Outcomes

  • Control and accountability — you can explain what’s in use, what leaves the company, and who owns it.
  • Clear boundaries and options — separation between internal data and external services, without accidental lock-in.
  • Fewer unpleasant surprises — reduced risk of data leakage, IP exposure, or unmanaged third-party processing.
  • A reversible operating model — inspectable, maintainable, reversible systems.

Start here

A short, paid assessment that turns “we’re using AI” into a decision-grade map: what’s in use, what leaves the company, and what must stay controlled.

You get:

  • Inventory of AI usage (who uses what, for what, and why)
  • Data movement map (what leaves the org, where, and under which terms)
  • Unacceptable outcomes + controls (what would be a headline)
  • Target boundaries (owned/internal deployment + separation points)
  • A phased plan (reversible, with clear ownership)

Next step: email me with 3 lines — where AI is used, what must not leave the company, and what you can’t afford to be wrong about.

Request the assessment

What this is

Most companies adopt AI through external platforms. That’s fast — and often irreversible.

I help teams deploy private AI systems that run in controlled environments, use internal data safely, and remain fully owned by the company.

In plain terms: you get AI capability without turning your data and operations into someone else’s platform.

For leadership, this is less a tooling decision and more a control decision. It reduces long-term dependency and the downstream risk created by unmanaged AI and infrastructure choices.

No hype. No lock-in. No data leakage.

When this makes sense

  • AI is already discussed or used internally
  • Sensitive data must not leave the organization
  • Cloud AI tools feel convenient but risky
  • Long-term control matters more than short-term speed

If you are just experimenting or looking for cheap tools, this is not a fit.

What I actually do

  • Internal AI deployments in controlled environments
  • Assistants and workflows built around your existing systems
  • Clear boundaries: what stays internal vs. what can be external
  • Access control, logging, and operational ownership
  • Automation that is reversible and maintainable

Systems are designed to be inspectable, maintainable, reversible, and fully owned.

Engagement

Most work starts with a fixed setup phase. If useful, it continues as a retained advisory / operations role to keep the system safe, controlled, and evolving.

  • Fixed setup to establish a controlled baseline
  • Optional retainer for ongoing oversight and improvements
  • Limited number of clients at a time

How I work

Small, focused engagements only. This work typically starts as a fixed setup and continues as a retained advisory role.

Direct work with technical leadership. No hand-offs. No junior layers.

About

Senior cybersecurity and infrastructure architect. Focus: privacy, automation, and system control.

This practice supports a high-trust consulting model built through direct conversations.

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