An Introduction to Distributional’s Platform

Adaptive testing is critical to support production-grade AI applications at scale. This enables AI teams to leverage behavioral distributions to create a comprehensive definition of an app’s desired behavior that can be refined over time. Thus enabling teams to quantifiably test and investigate when there are deviations from that desired behavior.

Distributional provides an enterprise platform for adaptive testing, which is designed to meet the scale and performance needs for AI teams to continuously test, understand, and refine application behavior. Using Distributional’s platform, customers are able to shorten the development cycles for AI, productize higher value applications, and keep them in production. All while minimizing risk to the business with the confidence that these applications are behaving and will continue to behave as desired. 

‍

Distributional’s platform was designed to easily integrate with existing tools and workflows, and to scale alongside AI teams and their projects. The architecture is intentionally streamlined to result in efficiencies and simplified management in the long run.

‍

This guide was written to help AI teams quickly get up to speed on Distributional’s architecture so they can hit the ground running. In the following pages, we’ll share key terminology, take a deep dive into the technical architecture, and review how it can integrate into existing architecture.