ATS

How Our ATS Team Works

At ATS, we help our customers extract information from data. These insights enable our customers to understand their systems and businesses better, so that better management decisions can be made.

Our data science capabilities have saved our customers tens of millions of dollars in OpEx and CapEx dollars, while reducing risk costs from operations.

Complete AI Driven Approach

We ensure our customers are equipped to navigate the age of AI with best-in-class data science, machine learning, and large language model capabilities.

Our data science engine utilizes the state-of-the-art in data science methods, and we keep our pulse on the latest academic research to ensure that the best techniques are applied.

Our data science capabilities have saved our customers tens of millions of dollars in OpEx and CapEx dollars, while reducing risk costs from operations.

Complete AI Driven Approach

We ensure our customers are equipped to navigate the age of AI with best-in-class data science, machine learning, and large language model capabilities.

Our data science engine utilizes the state-of-the-art in data science methods, and we keep our pulse on the latest academic research to ensure that the best techniques are applied.

Our data science capabilities have saved our customers tens of millions of dollars in OpEx and CapEx dollars, while reducing risk costs from operations.

Questions

Our Data Science Capabilities Enable Our Customers To Answer Tough Questions

ATS was able to build an optimization model that informed a utility how to spread constrained maintenance dollars across their network of over 500 substations for circuit breaker maintenance. As a result, the utility benefited from overall life extension of their breakers and fewer failures, at lower cost. Surplus budget was redirected to maintenance of other high priority assets.
ATS built a decision support tool, based on reinforcement learning models, that informs satellite system operators of large systems when to deploy new satellites. This capability minimizes risk costs from failure, while also minimizing excessive spare so that overall costs are minimized.

ATS trained advanced AI models to predict future outages and ignitions based on assessed probabilities of failure, asset characteristics, and climate. These models accurately identified high-failure circuits and were nearly ten times more accurate in predicting ignitions compared to random sampling.

ATS developed a well-calibrated stochastic model to represent a disease outbreak and subsequent response in an urban area. By training machine learning models on the results of the stochastic model, we could evaluate thousands of possible outbreak and economic scenarios in seconds. This enabled agile epidemic response and provided cost-effectiveness information for public health decision makers.