Meet Shelf at Microsoft Ignite, Chicago, November 19–22
How to Make Your Sharepoint Data AI-Ready: image 1

How to Make Your Sharepoint Data AI-Ready

Getting your SharePoint data AI-ready isn’t just about flipping a switch. It’s about taking a closer look at the data you already have and setting it up for success. Whether you’re aiming to streamline workflows, unlock actionable insights, boost the user experience, or simply make better use of...

Read More
How to Make Your Sharepoint Data AI-Ready: image 2

How to Prevent Microsoft Copilot From Giving Bad Answers

Microsoft Copilot is a powerful tool, but like any AI, it can provide incorrect or misleading answers. To ensure you’re getting the most accurate responses, it’s essential to understand how to prompt Copilot properly in order to prevent bad outputs.  Let’s explore how Microsoft...

Read More
How to Make Your Sharepoint Data AI-Ready: image 3

Knowledge Base AI Chatbots: What They Are and How to Build One

In a world where users expect fast, accurate answers, knowledge base AI chatbots offer an efficient solution. By integrating artificial intelligence with your existing content source, these chatbots help users find information instantly, minimizing the need for human support.  This guide will...

Read More
How to Make Your Sharepoint Data AI-Ready: image 4

AI Knowledge Base: Everything You Need to Know

AI knowledge bases are changing the way organizations manage and access information. These AI-powered systems can understand user intent and deliver faster, more accurate results while learning and improving over time.  In this guide, we’ll explore how AI knowledge bases work, their key...

Read More
Midjourney depiction of structured and unstructured data in relation to knowledge graph

Seamlessly Link Structured and Unstructured Data with a Knowledge Graph

A knowledge graph is a structure that connects diverse pieces of information, helping you uncover relationships and insights that might not be immediately apparent. In some cases, you need to bridge two types of data together: structured and unstructured data. In this article, we provide a clear,...

Read More
How to Make Your Sharepoint Data AI-Ready: image 5

How Shelf Makes Salesforce AI Reliable

What is Retrieval-Augmented Generation? Retrieval-Augmented Generation (RAG) is a Generative AI (GenAI) implementation technique that is accelerating the adoption of GenAI and Large Language Models (LLMs) across enterprise environments. By enabling organizations to use their proprietary data in...

Read More
How to Make Your Sharepoint Data AI-Ready: image 6

Generative AI Is the Poison and Antidote for Unstructured Data Quality

When it comes to data quality, unstructured data is a challenge. It often lacks the consistency and organization needed for effective analysis. This creates a pressing need to address data quality issues that can hinder your ability to leverage this data for decision-making and innovation. As you...

Read More
How to Make Your Sharepoint Data AI-Ready: image 7

Understanding Data Decay, Data Entropy, and Data Drift: Key Differences You Need to Know

We rely on data to inform decision-making, drive innovation, and maintain a competitive edge. However, data is not static, and over time, it can undergo significant changes that impact its quality, reliability, and usefulness.  Understanding the nuances of these changes is crucial if you aim...

Read More
How to Make Your Sharepoint Data AI-Ready: image 8

Why Generative AI Elevates the Importance of Unstructured Data

Historically, we never cared much about unstructured data. While many organizations captured it, few managed it well or took steps to ensure its quality. Any process used to catalog or analyze unstructured data required too much cumbersome human interaction to be useful (except in rare...

Read More
How to Make Your Sharepoint Data AI-Ready: image 9

How GenAI Transforms Every Aspect of Data Consumption and Interaction

From the Library of Alexandria to the first digital databases, the quest to organize and utilize information has been a reflection of human progress. As the volume of global data soars—from 2 zettabytes in 2010 to an anticipated 181 zettabytes by the end of 2024 – we stand on the verge of a new...

Read More
Midjourney depiction of an LLM receiving inputs

The Influence of LLM Inputs on Outputs

Large language models analyze datasets to derive patterns and rules as a method of learning and replicating human intelligence. As you can probably guess, the dataset used in a model can dramatically alter its understanding. We’ve used a number of analogies to explain the significance of this, but it boils down to the same principle: the inputs in LLMs greatly influence the outputs.

Read More
Get Demo