Imagine this: You run a data-driven driven fintech or healthcare company; you have access to a plethora of data, and could use new machine learning tools to better predict fraud or advance clinical research. Except, you can’t: the value and insights from the data are entangled in privileged customer data that make it difficult to access for your AI model.
How can you drive innovation with AI if you can’t use all of your data?
This is a recurring gap in machine learning. In fact, IDC reports that 43% of enterprise data can go unused, which takes away from the benefits of using ML/AI.
Protopia, a Texas-based AI company, has developed the “Stained Glass Transform™” software, which helps companies safely access more real data. Protopia AI aims to bridge the structural gap in data and ML by ensuring raw sensitive data is never exposed to AI in identifiable form, but the AI still gets everything it needs. The patented technology is based on discoveries made by Prof. Hadi Esmaeilzadeh, the Endowed Chair of Computer Architecture at UC San Diego, who is also the co-founder and CTO of Protopia AI.
Not Just Another Security Company: Enabling AI by Unlocking Quality Real Data
While the solution protects sensitive data, the end goal is to enable enterprises to leverage their data to the fullest to power AI. Protopia AI’s technology allows companies to more easily gather insight about data that was previously inaccessible. When training an AI model or just as importantly when using an already trained AI model – accessing the data you need is one of the biggest hurdles when it comes to sensitive data, and the data steward’s willingness to share that data.
Other providers in the space either focus solely on the training phase, which leaves the need for protecting sensitive information in deployment data unanswered, or require specialized hardware or new ML paradigms which makes them difficult to use. This makes it risky for teams to confidently use SaaS solutions for machine learning or share data with technology partners or even other departments in the same organization.
Protopia AI’s solution learns what AI models need, removes what it doesn’t, and obfuscates what it does need to the maximum amount – with minimal accuracy loss. This helps separate the value of the data for AI and the data ownership/control.
How Does Protopia AI Work?
Protopia AI’s Stained-Glass product transforms the data representation as it comes out of the data source/root of trust. The target machine learning algorithms do not see the original identifiable data and instead see a targeted randomized version of it that is only understandable to that specific and individual machine learning task. Their site also has a nifty demo anyone can try out.
Protopia AI works for any data type and any AI model with little overhead in the data pipeline at the edge, on-premises or in cloud-data platforms. The Stained Glass Factory™ software is an extension of a deep learning (DL) framework like PyTorch. Stained Glass Transform™ created by this product add a new layer of protection against leakage of sensitive information for and can be applied throughout the ML lifecycle: inference and training.
Protopia was built for chief data scientists, chief technology officers, chief data officers, and their teams who concentrate on improving the organization’s bottom line using ML/AI models. Protopia’s empowers its users to work with the CISO or CSOs of their organizations in further securing the control of their data in increasingly complex environments
The Cost of Not Using the Right Data in Machine Learning
AI has significant potential to enable organizations to unlock billions of dollars of value across multiple industries including finance, healthcare, enterprise technology and government. The value of using machine learning and AI is high. On the other hand, not using the right data and analytical tools impacts a wide range of industries in terms of financial loss and service disruptions that cannot be ignored. For example, banks deal with massive amounts of data in different inaccessible silos that prevent them from making informed decisions on threats such as fraud. Fraud is one of the biggest problems inflicting financial services, costing the sector nearly $42 BN a year, and where AI could provide massive efficiencies. To this end, global fintech, Q2 has been working with Protopia to unlock new data for finding fraud.
Q2 Uses Protopia for More Data, More Reach
With Protopia, Q2 accesses potential clients who were previously unapproachable due to internal data governance protocols restricting SaaS solutions. As Q2 explores offering new solutions, they find that utilizing the latest privacy-enhancing technologies as a centerpiece of their digital banking solutions enables them to not only meet their voice-of-customer-based needs but also greatly increases the accessibility of their solutions. The Q2 Sentinel team is using Protopia AI’s Stained Glass Transform™ to expand the adoption of their latest cloud-based Fraud Detection Solution to those clients that are underserved or unserved today by:
- Detecting fraudulent checks without the need to analyze plain check images and
- Work at the same level of accuracy as if it were using the plain check images.
“Protopia AI empowers enterprises to extract maximal value using AI and machine learning from their data by providing the governance and protection that is necessary.” said co-founder and CEO, Eiman Ebrahimi, PhD. Ebrahimi and Q2’s Chief Data Scientist are presenting Q2’s solution with data and AI leaders at the upcoming annual AI Summit in New York. Details of event are here.
Win All-Access Pass to AI Summit, NY + Exclusive Presentation: How Q2 Accesses New Users for Fraud Detection with Breakthrough AI. Enter here.
Note: Thanks to Protopia AI for the thought leadership/ Educational article above. Protopia AI has supported and sponsored this Content. For more information, products, sales, and marketing, please contact Protopia AI team at email@example.com
Asif Razzaq is the CEO of Marktechpost Media Inc.. As a visionary entrepreneur and engineer, Asif is committed to harnessing the potential of Artificial Intelligence for social good. His most recent endeavor is the launch of an Artificial Intelligence Media Platform, Marktechpost, which stands out for its in-depth coverage of machine learning and deep learning news that is both technically sound and easily understandable by a wide audience. The platform boasts of over 2 million monthly views, illustrating its popularity among audiences.