Discover more about AI security in enterprise and the related measures to mitigate AI risks.

Discover more about how AI agentic workflows will set a new standard for performance, accuracy, and productivity in enterprises.

For any enterprise looking to leverage AI, identifying, defining and measuring precisely its use cases, requirements, and potential ROI is a necessary step.

The introduction of AI promises a future of efficiency and productivity, but such a transformation requires a thoughtful approach, particularly with regard to your workforce.

Fine-tuning is a hot topic in the AI landscape, and the choice of data is particularly important. In this article, we present some risks and challenges of using proprietary data for fine-tuning your AI models.

Retrieval Augmented Generation (RAG) is a method that enhances the capabilities of LLMs by integrating them with a dynamic retrieval system. In this article, we will discuss what exactly is RAG, and how does it enhance the functionality of LLMs in real-world applications.

Large Language Models (LLMs) have shown great promise as highly capable AI copilots that are incredible at generating coherent and contextually relevant text based on given prompts and can assist in a wide range of tasks.  The use of open-source models offers a golden path, especially for organizations that don&

The time when AI-powered solutions were reserved for a small part of organizations with important resources and highly skilled team is over. Today, almost any organization can decide to apply Artificial Intelligence (AI) or Generative Artificial Intelligence (GenAI) to their business to unlock unprecedented efficiencies and innovations.  If the hype

In a business context, Large Language Models (LLMs) – used as a copilot for example – have the advantage of understanding any query and providing natural language relevant and helpful answers – just like any other colleague. Just think about ChatGPT. It is more likely that most of your employees are already using

Among the most talked-about advancements in AI is the emergence of Large Language Models (LLMs), complex algorithms that have the power to understand, generate, and interact using human language. LLMs are fundamentally reshaping our interactions with technology and the digital world at large. Large Language Models (LLMs) are sophisticated learning

In the ever-evolving technological landscape, terms like Artificial Intelligence (AI) and Generative Artificial Intelligence (GenAI) have transcended buzzword status to become foundational elements in contemporary discourse. However, with their increasing presence comes the growing need to understand what these terms entail. Artificial Intelligence (AI) “Artificial intelligence” (AI) is a broad

Understanding common AI terms is essential for harnessing the power of artificial intelligence in your business operations. This glossary is designed to help you navigate the often complex vocabulary of AI. Artificial Intelligence (AI): Artificial intelligence or AI is a broad term that refers to any type of computer software

The adoption of Artificial intelligence (AI) brings unprecedented advantages, ranging from enhanced efficiency to ground-breaking innovations. Data suggests for example that AI has the potential to boost employee productivity by approximately 40% by 2035 and AI in business has become a top priority for 83% of leading corporations today. The

Artificial Intelligence (AI) has already indelibly transformed our way to work (or if it hasn’t transformed yours yet, it will soon). At the heart of this transformation lies a key aspect of AI technology - the “prompt”. The prompt serves as a conduit between humans and AI, guiding intelligent