Distributional: Making AI Safe and Reliable
In today's technological landscape, AI systems have presented unique challenges. Traditional software testing methods fall short when it comes to dealing with the unpredictability, uncertainty, and unreliability of AI. This is where Distributional comes in.
Distributional is a proactive AI testing platform designed to give AI teams the confidence they need in the reliability of their AI and ML applications. It addresses the risks associated with AI products by providing a comprehensive solution throughout the entire AI software lifecycle.
One of the key features of Distributional is its framework that enables AI application teams to collect and augment data. This data is then used for testing, and the platform alerts on test results. Teams can triage these results and resolve any issues that arise. The dashboards provided by Distributional allow for detailed analysis of results, efficient triage of failures, and the capture of an audit trail for governance purposes.
Furthermore, Distributional's intelligence automates various processes such as data augmentation, test selection, and test calibration in an adaptive preference learning process. This not only saves time and effort but also ensures more accurate and efficient testing.
Another advantage of Distributional is its ability to be deployed in your VPC and fully integrate with your existing stack. This makes it a seamless addition to your workflow.
The team behind Distributional is passionate about solving the AI testing problem at an enterprise scale. They draw inspiration from their customers, partners, advisors, and investors, and are on a mission to make AI safe, reliable, and secure.
In conclusion, Distributional is a game-changer in the field of AI testing, offering a comprehensive solution to ensure the reliability and success of AI applications.
