Your Engineers Are Using ChatGPT. Do You Know Where Your IP Is?

It is 2:00 PM on a Tuesday. Your Lead Engineer is struggling with a complex Python script for a new quoting algorithm. To save time, they copy the code block containing proprietary margin data and paste it into a public AI chatbot.

“Debug this code for me,” they type.

In three seconds, the AI fixes the code. Productivity goes up. But in those same three seconds, your company’s intellectual property just left your firewall, crossed a public server, and potentially became training data for a model anyone else can use.

This is Shadow AI, and it is happening in your company right now.

The Innovation Trap

We cannot pretend AI isn't useful. It is the single biggest productivity multiplier since the internet. For manufacturers in the Oak Ridge Corridor, AI can automate quoting, predict inventory shortages, and optimize supply chains.

But for companies handling Controlled Unclassified Information (CUI) or proprietary manufacturing processes, the "Public Cloud" is a minefield.

Most public AI models (like the free versions of ChatGPT, Claude, or Gemini) operate on a simple trade: You get free intelligence; they get your data.

If you are a government subcontractor subject to CMMC 2.0 or ITAR, pasting that data into a public model isn't just a security risk - it’s a compliance violation. You just leaked CUI to a third-party server you do not control.

The "Ban It" Strategy Doesn't Work

Many owners react by banning AI entirely. They block the URLs and tell staff, "Don't use it."

This fails for two reasons:

1. Staff will bypass it. They will use their personal phones or hotspots because the tools make them 10x faster.

2. You lose your edge. If your competitors are using AI to bid faster and design smarter, and you aren't, you will be priced out of the market.

The Solution: "The Enterprise Wrapper" vs. "The Enclave"

At Attenity, we believe the answer isn't Abstinence - it’s Governance. We help manufacturers deploy compliant AI using two distinct strategies, depending on your risk profile.

Path 1: The Enterprise Wrapper (Speed & Power)

For most commercial manufacturers, the solution is Private Cloud Access. We don't send your employees to chatgpt.com. Instead, we connect your systems to Azure OpenAI or AWS Bedrock.

• How it works: We build a secure, encrypted tunnel from your office to the enterprise cloud.

• The Guarantee: Unlike the consumer versions, these enterprise agreements include "Zero Retention" policies. Microsoft and Amazon contractually guarantee that your data is never used to train their models.

• The Result: You get the full brainpower of GPT-4 or Claude 3.5, but your secrets stay secret.

Path 2: The Local Enclave (Maximum Security)

For highly regulated environments (ITAR/Top Secret), we deploy Local LLMs.

• How it works: We install a dedicated AI server inside your physical facility. The "Brain" lives on your rack, not in the cloud.

• The Guarantee: The data physically cannot leave your building.

• The Result: Total air-gapped security for your most sensitive CUI.

Stop Guessing. Measure the Risk.

You cannot secure what you cannot see. The first step to a Responsible AI strategy is finding out where your "leakage points" are right now.

Are your sales reps pasting customer emails into AI to write responses? Are your devs pasting proprietary code?

We designed the Manufacturing AI Readiness & Risk Assessment (MARRA) to answer these questions. In three weeks, we map your data flow, identify Shadow AI usage, and build the roadmap for a secure, private AI pilot.

Don't let "Shadow AI" leak your trade secrets. Bring the intelligence inside the walls.

Ready to innovate without the risk?  Contact Us Today