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One of the groundbreaking advancements of late in AI is Retrieval-Augmented Generation (RAG), which combines large language models (LLMs) with external knowledge bases to produce more accurate and contextually relevant responses. However, the implementation of RAG systems brings forth new challenges that necessitate robust evaluation models. This article delves into the importance of having an evaluation model when implementing RAG in a business context.

This blog highlights how thoughtful UX and UI design are essential drivers in the ongoing journey of software modernization, enabling organizations to improve usability, productivity, and business outcomes through iterative assessment, collaborative development, and a focus on user needs.

A personalized web experience doesn’t mean using everything you’ve gathered about someone to greet them by name, summarize their engagement with your brand and so on. Sometimes the subtlest variations in the experience can make a visitor or user feel more comfortable and satisfied.

An AI agent refers to a software entity that performs automated tasks on behalf of humans or other systems. These agents are programmed to make decisions and take actions based on their environment and predefined goals. In the context of AI and machine learning, agents often leverage algorithms to analyze data, learn from outcomes and improve their performance over time, often more efficiently than a human could.

Learn why this legal professional believes the future of legal work is hybrid—where AI streamlines admin tasks, but humans remain essential for high-stakes decisions and precision.

Progress OpenEdge ABL is a business-focused, fourth-generation language that enables rapid, reliable and scalable development of mission-critical applications, making it a trusted and future-ready choice for organizations and developers.

This is the third and final article in our series following DataVault’s implementation of Progress' RAG-as-a-Service platform, Progress Agentic RAG.

This article explores how to built sophisticated data pipelines, connect multiple sources and create AI-powered systems that transform scattered information into actionable intelligence—all while facing a critical compliance deadline.

What exactly is a vector, and more importantly, why should you care? In simple terms, a vector is a numeric representation of data. For example, a paragraph of text, an image, or even a sound clip can be transformed into a vector, which is a series of numbers that capture its meaning, context or features. Vectors allow computers to “understand” unstructured data and compare it in ways that traditional databases cannot, both of which are foundational to AI.