By Aubrey Merchant-Dest Artificial intelligence (AI) is rapidly transforming industries, with finance being at the forefront. From fraud detection to algorithmic trading, AI is making waves. But with great power comes great responsibility, and in the realm of finance, trust and risk management is paramount. This is where AI transparency and explainability (XAI) come into … Continued

By Loris D’Acunto Revolutionizing Banking Communications In the highly regulated world of investment banking, the accuracy of machine learning models and how they are trained is a crucial aspect that cannot be underestimated. Large language models often have trouble when used in specific areas like finance, especially if they’re not trained on the detailed types … Continued

By John Suit In the evolving landscape of financial services, the surge in data complexity demands innovative approaches to data management. Semantic technologies, particularly ontologies and knowledge graphs, have emerged as key players in navigating this intricate data maze. But what sets them apart, and how do they complement each other in enhancing data understanding … Continued

By Aubrey Merchant-Dest Risk management is a critical aspect of any business, but it is especially important in regulated industries such as healthcare, finance, and legal. In this blog post, we will explore how sources and methods can be used as a framework for risk management in SaaS applications for regulated industries. Sources and Methods … Continued

By John Suit In the complex world of regulated industries, from finance to healthcare, the integration of Retrieval-Augmented Generation (RAG) with Neuro-Symbolic AI is setting a new standard for intelligent systems. This innovative approach not only elevates traditional AI capabilities but also introduces unparalleled precision and contextual insight, crucial for navigating the stringent regulatory landscapes … Continued

By Konnor Willison Managing the lifecycle of AI and machine learning models in production requires specialized practices and tools distinct from traditional software development. This is where MLOps steps in. Much like DevOps, MLOps abstracts away the mundane tasks, allowing ML engineers to focus on what they excel at: algorithm development. However, MLOps isn’t merely … Continued

Ask complex questions of your unstructured content and processes to get the right answers, at the right time.

By Steve Shillingford and Armen Sargsyan A friend of mine recently took me for a ride in his new Telsa. It was a wonderful experience. The design is sleek and modern, the ride was quiet and smooth, and the interior really convinced me that, rather than a car with modern features, it’s really a computer … Continued