In head-to-head comparisons, Text IQ returned more accurate results than the top three cloud provider APIs
Text IQ, a Top 100 AI company applying artificial intelligence (AI) to identify sensitive data, announced today that its solution for identifying personal information outperformed AWS, Microsoft and Google in a real-life comparison of AI recall and precision.
As companies across the globe are under siege by bad actors and must constantly remain vigilant against data breaches, Text IQ’s AI has proven to be fundamentally superior at recognizing social security numbers, health records, account numbers and other sensitive data – all while requiring substantially less human review and expense.
Recommended AI News: PatientKeeper Integrates its Mobile App with MEDITECH Expanse Hospital EHR System
The finding is significant because in the event of a data breach, which could easily encompass thousands or millions of documents, companies must both quickly and completely determine the type of personal information compromised. Using AI solutions with poor recall means missing too many instances of personal information, and employing AI with poor precision means countless hours of human review of all the false positives.
“We’re thrilled that Text IQ’s AI solution for identifying personal information not only outperformed the top cloud providers, but did so in dramatic fashion,” said Apoorv Agarwal, Text IQ CEO and co-founder. “Creating a system that searches great volumes of unstructured data sources while requiring a minimum of human review is a tough technical hurdle to overcome. But Text IQ’s talented staff of engineers succeeded in designing and building a solution demonstrably better than those offered by some of the world’s largest technology companies.”
As part of Text IQ’s continuous effort to improve AI solutions, the company compared its performance against some of the biggest players in the sector: AWS (Macie and Comprehend), Google (Cloud Data Loss Prevention) and Microsoft Azure (Text Analytics). The real-life dataset, provided by a willing client eager to help support this type of research, included 12,287 documents that had undergone AI and human review and were known to include personal information. The evaluation measured the percentage of relevant documents returned from the search process by Text IQ’s Brain and the APIs from the three cloud providers.
Recommended AI News: Endeavor Energy Resources Continues to Modernize its Operations with Datadobi
The test found Text IQ was twice as effective in returning the relevant personal information, with an F-Score of 60%, compared with Google (34%) and Azure (30%), and was three times better than AWS solutions Macie (23%) and Comprehend (20%).
The problem for many solutions on the market is that they solve for broad, generic cases – casting a wide net. The result is they over capture and the data quality is very imprecise. These tools were built for general purposes. In contrast, Text IQ created a tool precisely to solve this kind of identification problem while reducing human input and costs.
“People have a reasonable expectation that the companies they do business with will do everything they can to protect their privacy,” said Omar Haroun, Text IQ co-founder and COO. “Unfortunately, when a breach occurs, even companies with the best intentions don’t have the technology to do a fast and accurate search for sensitive information. With our demonstrably better approach, companies get a more accurate result, faster and at less cost.”
Recommended AI News: Gilded Launches Mass Pay, Enabling Businesses to Pay Employees in Crypto
Comments are closed.