As AI moves from hype to measurable results, one truth is becoming clear: Enterprise AI needs business context to be fully ...

The SEC's 2026 examination priorities emphasize existing regulatory expectations extended to technologies that didn't exist ...

When AI can explain its why, not just its what, hospitals can have greater success in adopting these tools at scale.

Traditional rule-based systems, once sufficient for detecting simple patterns of fraud, have been overwhelmed by the scale, ...

Explainable AI plays a central role in validating model behavior. Using established explainability techniques, the study examines which financial variables drive fraud predictions. The results show a ...

In recent years AI has emerged as a powerful tool for analyzing medical images. Thanks to advances in computing and large medical datasets from which AI can learn, it has proven to be a valuable aid ...

This article explores the potential of large language models (LLMs) in reliability systems engineering, highlighting their ...

The appointment, effective January 4, 2026, represents a strategic milestone in Seegnal's mission to build the Intelligence Layer of Prescriptions and to accelerate the development of Seegnal Guard, ...

In recent years, AI has emerged as a powerful tool for analyzing medical images. Thanks to advances in computing and large medical datasets from which AI can learn, it has proven to be a valuable aid ...

Financial services data leaders face a fundamental paradox: they have unprecedented access to data assets, yet they continue ...