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The Inference Privacy Layer for AI Factories Neo Clouds Sovereign AI AI Agents

Secure multi-tenant inference without hardware isolation: unlock sensitive data and lower TCO

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Encryption ends where AI begins

At inference, your data is plaintext at the model host — exposed in logs, memory, and observability tools
  • This isn't a misconfiguration. Data must be decrypted for the model to process it, no amount of transport or storage encryption closes this gap.
  • That forces organizations to restrict what data AI can use and where models can run, limiting AI to low-value use cases or forced onto dedicated infrastructure that drives up cost.
  • Protopia Stained Glass eliminates this tradeoff by removing plaintext exposure risk, making any compute available to high-value/sensitive workflows.

Half your AI Factory is sitting idle

Privacy and compliance requirements force large granularity GPU carveouts for every sensitive workflow. The result: expensive infrastructure sitting idle between inference requests or AI restricted to the data that’s easiest to clear, not the data that drives the most value. 

Whether you run an enterprise AI hub, a sovereign cloud, or a managed inference platform — this is why your GPUs are sitting idle. 

Multi-tenant scheduling alone doesn’t solve this: it controls who gets compute, not who can see the data flowing through it.

Protopia Stained Glass enables private, multi-tenant inference, no hardware isolation required. More tenants served, more tokens processed, better economics at scale.

NVIDIA AI Factory Reference Design

INFERENCE PRIVACY LAYER

What the Stained Glass inference privacy layer unlocks​

Deploy sensitive data use cases faster, cheaper, and privately on any infrastructure

Paying the data, infrastructure, and deployment tax:

With Protopia Stained Glass inference privacy layer:

Your most valuable data is walled off from AI or degraded by de-identification.

With Protopia Stained Glass

Sensitive data flows into AI pipelines at full fidelity, no exposure.

Sensitive workloads are locked to isolated large-granularity compute regardless of utilization.

With Protopia Stained Glass

Deploy on any infrastructure, including managed, multi-tenant.

Every sensitive use case carries extra compliance cycles, procurement friction, and isolation requirements.

With Protopia Stained Glass

Accelerate deploying sensitive data workflows like any other workload.

Use cases killed because the cost math doesn't work

With Protopia Stained Glass

Use cases evaluated on business value, not infrastructure cost

Protopia Stained Glass

Created in post-training. Deployed on any infrastructure.

Stained Glass Transform (SGT) replaces raw data with model-specific, randomized representations — usable only by the target model, with no changes to the model or serving stack. SGT is trained in a post-training step that enables the unmodified model to operate accurately on randomized representations, eliminating raw data from inference entirely. 

Encryption, masking, tokenization, and confidential computing can complement this but none can achieve it alone.

How Stained Glass Works

Read The Whitepaper

“At Q2, we offer a variety of fraud detection solutions using AI; for example, we use computer vision to detect various forms of check fraud. The prospect of feature-level obfuscation of inbound data for maximizing data protection and privacy in our AI solutions is very compelling to us and to our customers.”

Jesse Barbour

Chief Data Scientist
Q2 Banking

Partner Video: Scaling AI Fraud Detection

“The use of LLMs and GenAI will only accelerate the migration of sensitive data into the cloud… This is not a problem that traditional data security provider can solve. Luckily there are really smart people working on this like the folks at Protopia.”


James Beecham

Founder and CEO, ALTR

Partner Blog: Data Security for GenAI

“Being able to quickly adopt newer versions of Llama as they are released enables us to innovate and lead. With paid/closed models, we’d be waiting for procurement cycles and appropriations. With Llama, we can invest our budget in making our GPT solution faster, more capable and secure.”

Vince Kellen

Chief Information Officer 

University of California, San Diego

Case Study: Secure AI Agents at UC San Diego

“A big concern has emerged in AI: data privacy. Protopia uniquely addresses those concerns and accelerates time to AI deployments and value. NetApp is thrilled to have Protopia in our NetApp AI solutions as a technology partner.”


Keith Norbie

Sr. Director WW Partner

Solutions & Sales Acceleration

Partner Blog: Confidential Inferencing

Take the first step

Find out how private inference powered by Protopia Stained Glass can transform your AI efforts.

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Enterprise Guide to
AI Security

A practical guide to deploying privacy-preserving AI at scale, from infrastructure to data governance.

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Protopia Tech Docs

Read the technical deep dive on how SGT works, benchmarks, and integration patterns.

Read the Docs