Private AI
Private AI vs public ChatGPT and Copilot
They can do similar things. The difference that matters is who controls your data, what terms protect it, and how much of it the tool can see. Here is a fair comparison, and when each one is the right tool.
The short version
Public tools like ChatGPT, Copilot, and Gemini process whatever you paste in, on the vendor’s terms, with little visibility for you. Private AI is deployed in your business: your documents stay in your systems, only what a task needs is sent to enterprise-grade models under strict no-training terms, and you control access with a full audit trail. And when requirements demand it, we run private models fully locally on NVIDIA DGX Spark hardware, so nothing leaves your network at all. For general, non-sensitive work, public tools are excellent. For client records, regulated data, or anything you could not paste into a public chatbot, private AI is the safer call. Most businesses end up using both.
Side by side
Public AI vs private AI
No strawman. Public tools are powerful and improving fast. This is about fit, not which is "better."
Where your data is processed
Public AI (ChatGPT, Copilot)
In the vendor’s cloud (OpenAI, Microsoft, or Google).
Private AI (Shield)
Your documents live in your systems. Only what a task needs is sent to enterprise-grade AI models, also cloud-hosted, under strict no-training terms. Or go fully local on NVIDIA DGX Spark hardware, where nothing leaves your network at all.
Used to train outside models
Public AI (ChatGPT, Copilot)
Business tiers generally exclude training, but reading and holding the vendor to those terms is on you.
Private AI (Shield)
Never. No-training terms are a condition of every model we deploy, and we put that in writing.
Knows your business
Public AI (ChatGPT, Copilot)
General knowledge, plus whatever context you paste in each chat.
Private AI (Shield)
Grounded in your documents, policies, and history.
Access control and audit
Public AI (ChatGPT, Copilot)
Vendor-defined, with limited visibility for you.
Private AI (Shield)
Role-based access with a full audit trail you own.
Works across your tools
Public AI (ChatGPT, Copilot)
Strongest inside its own ecosystem.
Private AI (Shield)
Connects to the tools you already use.
Who manages and secures it
Public AI (ChatGPT, Copilot)
You, plus the vendor’s defaults.
Private AI (Shield)
Shield sets it up, guard-rails it, and monitors it.
Best for
Public AI (ChatGPT, Copilot)
General, non-sensitive, everyday tasks.
Private AI (Shield)
Sensitive data, client confidentiality, compliance, internal automation.
When public AI is the right tool
Honestly, for a lot of day-to-day work it is, and we will tell you when.
- Drafting general content and brainstorming
- Learning something new or summarizing public material
- Coding help and quick research
- Anything that is not confidential or client-specific
When private AI earns its place
The moment your data is sensitive or specific to your business.
- Client, patient, legal, or financial records
- Work that must meet PIPEDA or provincial health privacy rules
- Proprietary processes and institutional knowledge
- Automations wired into your internal systems
How Shield does private AI
Hermes Agent and OpenClaw
Hermes is an always-on internal AI agent that answers questions and automates routine work. OpenClaw is a private AI workspace for your team. Both are deployed in your environment and fully managed by us.
FAQ
Common questions
Is ChatGPT safe for business data? +
It depends on the tier and the data. Consumer ChatGPT can use your conversations to improve its models, and even on business plans, reading and enforcing the data terms is on you. For general, non-sensitive work it is fine. For client records, health, legal, or financial data, a managed private deployment, where your documents stay in your systems and only what a task needs is sent to enterprise-grade models under strict no-training terms, is the safer choice.
Does Microsoft Copilot keep our data private? +
Microsoft 365 Copilot keeps your data inside Microsoft’s cloud and states it does not use your business data to train its foundation models. That is a real boundary. The difference is where your documents live and who holds the audit trail: with Copilot they sit in Microsoft’s cloud on Microsoft’s terms, and Copilot works mainly inside the Microsoft ecosystem. Private AI keeps your documents in your own systems, sends only what each task needs to enterprise-grade models under strict no-training terms, and works across all your tools.
What is private AI? +
Private AI is a capable AI assistant deployed inside your business rather than used as a public web service. Your documents stay in your own systems, access is role-based and audited, and it is grounded in your own data. When it works on a request, it sends only what that task needs to enterprise-grade AI models under strict no-training terms, or, when requirements demand it, runs private models entirely on local hardware. Shield deploys these as Hermes Agent, an internal AI brain, and OpenClaw, a private AI workspace.
Can private AI run fully on-premises, with no cloud at all? +
Yes. We build and deploy private AI on NVIDIA DGX Spark systems that run the models locally, so inference happens inside your network and nothing goes to a cloud API. Most businesses do not need that level of isolation, and enterprise cloud models under no-training terms deliver more capability per dollar. But for strict data-residency rules, regulated environments, or clients who simply want it all in their own walls, fully local is on the menu. We help you choose based on requirements, not hype.
Do we have to choose one or the other? +
No, and most businesses should not. Use public tools like ChatGPT or Copilot for general tasks, and use private AI for anything sensitive or specific to your business. We help you draw that line and set both up safely.
What about staff who are already using ChatGPT on their own? +
In most businesses they already are, often with company data, and that is the real risk: unmanaged AI use nobody can see. Banning it rarely works. The fix is an AI usage policy plus a private alternative that is genuinely good, so people stop needing workarounds. We help with both.
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