Topia Awarded New Patent for Machine Learning Models to Identify and Use Seasonality Trend Data

Topia, the world’s leading global talent mobility and distributed workforce platform, announced that it has been awarded a new patent – Apparatus and methods of unsupervised machine learning models to identify seasonality and predicting seasonally-influenced metric values.

With AI and machine learning now being adopted more widely across a wide range of technologies designed for HR, compliance and finance professionals, this patent demonstrates Topia’s ongoing commitment to innovation and sets the company up to integrate machine learning models into products and solutions in upcoming releases, wherever it thinks this will provide value for clients.

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The patent centers around the use of data related to seasonality. Seasonality is a phenomenon where the values of a certain metric tend to follow a repeating pattern over time. Machine learning models can be used to both identify this seasonality, as well as to predict values for the metric based on the season. This can then be applied in several different ways, such as forecasting demand, predicting prices or anticipating customer or user behavior.

In the context of Topia’s solutions, one of many possible applications could be to predict flight rates to help customers better manage the flow of people movement in the business or to manage travel costs more efficiently.

“Our new patent shows that we continue to be at the forefront of technological innovation in the global mobility, travel compliance and distributed workspace,” said Shawn Farshchi, CEO at Topia. “With the rise of AI in almost all facets of business life, this patent provides us with the ability to substantially expand Topia’s platform with machine learning algorithms across our microservices, and further enhance our workflow automation.”

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