Shelf Blog
Get weekly updates on best practices, trends, and news surrounding knowledge management, AI and customer service innovation.
Once again, we’ll be exploring the topic of AI agents because more often we see phrases like “the AI agent isn’t working” or “the AI agent broke down”. Let’s be honest: most of the time, they break down or don’t work properly not because you chose a bad model, but because they’re running on...
Many people mistakenly believe that knowledge management is some system you can simply buy and turn on. But in reality, it is a complex, continuous, cyclical process: capture knowledge, organize it, store it, share it, use it, update it, and repeat the cycle. However, if even one step is skipped...
A traditional knowledge management system operates on a single principle: store and wait. One person creates an article, another searches for it using keywords and the article may or may not surface . AI-based knowledge management systems work differently. Unlike traditional systems, it doesn’t...
Ask ten people what knowledge management is, and you’ll most likely get ten different answers. And it’s not even that people simply don’t know what it is, it’s just that everyone has their own idea of it. Some think it’s a process, some think it’s a wiki, some say it’s a business, a platform, a...
A knowledge base for a team of 10 people is fairly simple. Just a few folders, everyone knows where everything is, and one person keeps it up to date. But when your company reaches the enterprise level, everything starts to change. Just imagine: thousands of people, dozens of owners, possibly...
Most knowledge bases don’t die from a lack of content, but they begin to deteriorate fairly quickly when there is no sense of ownership. A typical scenario: You’ve written an article, but it’s unclear who will be responsible for keeping it up to date. You updated a policy, but no one deleted the...
In the field of customer support, there’s one aspect that no one pays attention to: the sheer volume of data. When a customer asks a question, the answer can be found in completely different places: one in Confluence, another in a two-year-old Google Doc, and a third in the head of a senior agent...
Most knowledge management systems were created with a single purpose: to store information. But when it came to finding a specific document, you had to do it yourself. Reading through about 40 pages of policy to answer just one customer question was also your responsibility. Fortunately, times are...
Imagine this: a company purchases an expensive knowledge management platform. Everything seems to be going well, but six months later, the owner discovers that half the team simply isn’t using the platform. And it’s not the platform’s fault, it’s a good one; it’s just suited for different tasks....
Every IT team has run into this problem at least once: a major outage occurs, the person in charge sets out to find the cause, a couple of hours go by, and they finally find a solution. Later, it turns out that their colleague had closed an exact copy of that ticket three weeks earlier. In other...
Recently, companies were cautiously adopting Generative AI, which at the time seemed to represent the pinnacle of artificial intelligence. It’s writing text, creating images, and providing quick responses. This worked well, until organizations recognized a fundamental gap: generating responses is...
We’re willing to bet that when you implement an AI agent, you expect it to speed up processes and lighten your employees’ workload. You watched sleek and impressive demos where the agent responded instantly and found the information you needed. But in reality, things turned out a little...