Torch.AI today announced the company has joined Insurtech Vanguards, an initiative led by Guidewire, a leading Property & Casualty (P&C) cloud platform provider. With this, Torch.AI will bring data and artificial intelligence (AI) capabilities to insurance organizations across the insurance value chain. Guidewire's Insurtech Vanguards program is an initiative to help insurers learn about solutions from leading insurtechs and how to best work with them. As part of the program, Torch.AI joins one of the most reputable software providers in the insurance industry today to bring unique enterprise-level data infrastructure technology to a large and growing network of Guidewire customers and partners. "The large majority of insurance organizations today have not been able to optimize data usage across the business, still relying on error-prone, manual processes and complex point solutions," said Jason Eidam, Torch.AI's VP of Commercial Markets.

Data infrastructure artificial intelligence company Torch.AI has won a five-year contract from the U.S. Navy to provide next-generation AI and data infrastructure software capabilities for the Navy's Digital Warfare Office (DWO), the company announced in a statement. The company will provide AI and machine-learning capabilities that are intended to allow the Navy to "better operate and maintain their operational fleet across a complex, siloed IT environment including cloud compute, storage, hardware, and cloud edge devices used for data lakes at unclassified, secret, and top-secret levels," the statement reads. The DWO was established in 2016 to better utilize the data that Navy platforms collect. Torch.AI will be responsible for combining proprietary sensor, vessel, and other maritime data sources from multiple Navy platforms into "commercially consistent data payloads," the statement reads.

Business processes evolve over time to adapt to changing business environments. This requires continuous monitoring of business processes to gain insights into whether they conform to the intended design or deviate from it. The situation when a business process changes while being analysed is denoted as Concept Drift. Its analysis is concerned with studying how a business process changes, in terms of detecting and localising changes and studying the effects of the latter. Concept drift analysis is crucial to enable early detection and management of changes, that is, whether to promote a change to become part of an improved process, or to reject the change and make decisions to mitigate its effects. Despite its importance, there exists no comprehensive framework for analysing concept drift types, affected process perspectives, and granularity levels of a business process. This article proposes the CONcept Drift Analysis in Process Mining (CONDA-PM) framework describing phases and requirements of a concept drift analysis approach. CONDA-PM was derived from a Systematic Literature Review (SLR) of current approaches analysing concept drift. We apply the CONDA-PM framework on current approaches to concept drift analysis and evaluate their maturity. Applying CONDA-PM framework highlights areas where research is needed to complement existing efforts.