Stained Glass for Model Deployment
Deploying AI systems in production introduces unique vulnerabilities that training environments don’t face. Customer data flows through production models, which creates additional data privacy risks.
Protopia Stained Glass adds an essential privacy layer to model deployments that transforms data before model interaction, ensuring data remains protected without compromising the model performance your business depends on.
data protection at inference
Maximize Data Protection While Maintaining Model Accuracy
Critical business decisions rely on AI inference processes that require real, unaltered data for maximum precision. Protopia Stained Glass secures your sensitive information at the deployment phase while preserving AI model performance and accuracy.
Uncompromised Accuracy
Transform raw data into secure data representations that preserve model-relevant information
Lightning-Fast Protection
Decouple sensitive data ownership from Al infrastructure, keeping to maintain data privacy
Deployable Anywhere
Runs natively on all compute platforms to maximizing flexibility while reducing costs.
Protect Enterprise Data at Inference
Transform sensitive data into AI-compatible stochastic representations withnear-zero latency. Protopia Stained Glass Transform enables secure AI inference across on-premise, hybrid, and cloud environments while ensuring raw data is never exposed to models or users.
Preserve model accuracy
Secure ML Models for Text, Image, and Structured Data Deployments
Protopia Stained Glass preserves privacy throughout ML inference pipelines, protecting sensitive data like PII, IP-sensitive information, and proprietary information from data leakage and exposure. By using stochastic transformation, Protopia enhances inference security without sacrificing performance or requiring changes to your models or infrastructure.
Protopia AI with Natural Language Processing for Spam Detection
Natural Language Processing (NLP) tasks can consume data that contains sensitive information, such as confidential email communications. Protopia AI’s Randomized Re-Representations, shown on the right, enable NLP tasks to identify spam, but also scan all communications to protect confidential information.
Protopia AI with Tabular Data in a Loan Application
A model scanning tabular data in raw form exposes sensitive information such as Personal Identifiable Information (PII). Stained Glass enables models to read a completely transformed and randomized piece of data while retaining the same level of predictive accuracy. The reconstructed information of text and numbers does not match the data depicted on the left.
Protopia AI for Facial Recognition
Most AI facial recognition models see fully exposed images, which may contain sensitive information. With Stained Glass Transform™, the model sees a completely Randomized Re-Representation on the right while performing accurate inferencing with minimal information
CASE STUDY: FRAUD DETECTION
Q2 uses Stained Glass to develop new product for fraud detection
Financial services technology company Q2 wanted to maximize data protection for their new fraud detection product. Market research suggested they would increase the product’s desirability if it could operate without receiving raw check images. Q2 turned to Protopia AI’s Stained Glass Transform, which allowed their computer vision models to scan check images accurately without clients having to share raw check image data.
Reduce Friction in Enterprise Data Access for GenAI
Protect your sensitive data at LLM inference endpoints with stochastic transformations that preserve utility for target models while remaining unintelligible to humans and other AI systems.
CASE STUDY: COMPUTER VISION
US Navy leverages Stained Glass for maximum data protection in computer vision applications
Protopia AI partnered with NetApp and implemented Stained Glass Transform™ to demonstrate the breakthrough capability of being able to perform a task like real-time face recognition of VIPs without exposing unprotected images. This capability was showcased at the annual Trident Warrior exercise.
Facial Recognition for Identity Verification
The solution transformed subjects’ faces into Randomized Re‑Representations that were only readable by the facial recognition model with near‑perfect accuracy to identify VIPs. The use case showcased Stained Glass’ ability to protect real-time AI deployment successfully.
Securely unlock your sensitive data for AI
Stained Glass Transform (SGT) converts sensitive data and prompts into stochastic representations that improve accuracy, protect privacy and boost compute utilization to maximize your data’s AI impact.
TECHNICAL DOCUMENTATION
Run at blazing speed with Protopia Stained Glass
Explore Protopia’s technical resources to seamlessly integrate Stained Glass Transform (SGT) into your AI workflows.
Securely Build Open LLMs with Protopia AI Stained Glass Transform, accelerated by NVIDIA DGX Cloud
In this blog, we demonstrate how Protopia AI maximizes the protection of sensitive data when working with popular open-source models on NVIDIA DGX Cloud. We provide a step-by-step exploration of the technology and its implementations, along with performance benchmarks.
The Executive’s Guide to Secure Data & Impactful AI | Part 2
Welcome back to our three-part series designed by and for leaders in data, information technology, and AI. In the first installment, we tackled the critical issue of overcoming barriers to data accessibility, exploring strategies to unlock the full potential of your data assets while ensuring compliance and security.
The Executive’s Guide to Secure Data & Impactful AI | Part 3
This article, the final installment of our three-part series on secure data and impactful AI, outlines key principles and considerations to help you architect data systems and flows for secure and impactful AI.