Protect Proprietary Data When Sharing With AI
Sharing proprietary data with an AI vendor? A BAA and a "no training" promise are contracts, not architecture. Keep the data in your organization.
The promise problem
Every major AI provider will sign something for you. A Business Associate Agreement. A zero-retention addendum. A "we do not train on your data" clause in the terms of service.
All of these do one thing: they move your data to someone else's servers and then ask you to trust what happens next.
A BAA decides who is liable after something goes wrong.
It does not decide whether your data was exposed in the first place.
For client files, contracts, source code, financial models, and trade secrets, the question that matters isn't "what did they promise?" It's "where does my data physically go, and who can touch it?"
Follow the incentives
Frontier AI companies are in a race to build better models. Better models need better data. Your prompts, documents, and corrections are exactly the kind of high-quality, real-world data that improves a model.
That doesn't mean any given company is acting in bad faith. It means the incentive points one way, and the only thing holding it back is a policy. Policies change. Terms get updated. Companies get acquired. Legal holds and court orders can force retention no matter what the policy says.
Where the incentives sit
A model vendor gains something from having more data to work with. You have to trust that they don't act on it.
A provider that only leases you hardware and runs your models has nothing to gain from your data, because it never sees it.
What it exposes
When your data sits on a vendor's infrastructure, your protection is only as strong as their policy, their security, and their willingness to keep both unchanged. You have no way to verify any of it yourself.
A different model: your hardware, your models, your perimeter
The strongest protection is not a better promise. It's removing the third party from the picture. With Microve, that works like this:
You lease dedicated hardware
The machines are yours for the term of the lease. They aren't a slice of a shared multi-tenant cluster.
Models that keep no record and never train
The LLMs run on your hardware. They don't phone home, don't log to a vendor, and have no mechanism to learn from your data.
Everything is locally contained
Documents, prompts, and outputs all stay in the environment you control. Nothing is sent to a third-party API.
The Bottom Line
Your data doesn't leave your organization. It flows within it.
Why this goes beyond a BAA
A BAA is a reasonable safeguard when data has to leave your walls. Our approach is to make sure it doesn't have to. Here is the difference in practice:
With a third-party AI vendor
Your data travels to their servers and sits inside their retention window.
Protection depends on their policy, their staff, and their security holding up.
If something fails, you have a contract and a claim. The data is already out.
With Microve
Your data never leaves your organization, so there is no retention window to worry about.
Protection depends on your own access controls, which you can inspect and audit.
We have no incentive to look at your data, because we never receive it.
How to get started
You don't need to rebuild your stack. A practical path looks like this:
Map where your sensitive data goes today
List every tool your team pastes documents into, including the ones IT doesn't know about.
Move the sensitive workflows first
Contracts, client records, financials, and source code are the highest-risk tasks. Run those on hardware you control.
Give your team a tool that's easier than the leak
People paste into public chatbots because it's convenient. A private tool inside the workflow they already use removes the reason to.
What Microve provides
Microve builds and deploys AI automations that run entirely inside your environment, on hardware you lease and control.
No prompts sent to third-party APIs
Everything stays inside your organization.
No records kept outside your walls
No vendor logs, no external retention window, nothing to request deletion of.
No incentive to use your data
We don't build frontier models, so we have nothing to train and nothing to gain from your documents.
If your data is what makes your company valuable, it shouldn't depend on someone else's promise to stay yours.