Topia Granted Patent for ML Models Identifying and Using Seasonality Trend Data

Topia, a global talent mobility and distributed workforce platform, recently announced that it has been awarded a new patent for its unsupervised machine learning models, which can identify seasonality and predict seasonally-influenced metric values. This patent is a testament to Topia’s commitment to innovation and to incorporating machine learning models into its products and solutions in future releases, wherever it would benefit its clients.

The patent focuses on the use of seasonality-related data. Seasonality is a phenomenon in which the values of a particular metric tend to follow a repeating pattern over time. Machine learning models identify this pattern and forecast the metric’s values based on the season. This technique is applied in various ways, including predicting demand, forecasting prices, or anticipating user or customer behavior.

One potential application of this technology within Topia’s solutions is predicting flight rates to assist customers in managing the flow of people movement in their businesses or optimizing travel expenses. This new patent expands Topia’s current portfolio and demonstrates the company’s dedication to delivering entirely automated end-to-end Global Talent Mobility.

Shawn Farshchi, CEO at Topia, said, “Our new patent shows that we continue to be at the forefront of technological innovation in the global mobility, travel compliance and distributed workspace.” He further added, “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.”