How AI Solves the Biggest Problem with Knowledge Bases

Knowledge bases are a common component of customer support services. They’re designed to answer as many questions as possible, which eliminates the need for human agents in some situations. This can offer better customer support at lower costs, but there’s a big problem with this kind of solution: they lack real-world solutions.

The Problem with Knowledge Bases

Knowledge bases might be useful in letting humans find answers to their questions, but they’re not very efficient at it. Natural language questions require more than a boolean lookup. Humans can do this by matching the question in their mind to concepts they have stored.

Computers, however, struggle with this problem, which makes them unable to answer such human-like questions. Natural language AI helps solve the biggest problem with knowledge bases (the inability to match meaning) by working fluently with human language and concepts.

The biggest problem with today’s knowledge bases is the same one that existed when they were first invented: they’re boring. The facts and figures in a knowledge base are devoid of anything that might resemble a personality. They lack the spark of life.

Details about products, articles, or events are often presented in a list format. When you ask a question, you get an answer from a list. For example, if you ask Siri to find you a pizza place nearby, it’ll respond by listing off some local places. It’s up to you to figure out which one is closest or best for you.

In fact, that’s exactly how most people use Siri—to get quick answers to specific questions. The reason is simple: it takes too much effort to learn how Siri works and then apportion your requests appropriately.

It’s also very hard to remember every command and every nuance of the system; users have already complained about this issue in Amazon Alexa conversations. While we like to think of Siri and Alexa as super-powered AI assistants, they do act more like standard knowledge bases.

Using the Power of AI and NLP to Improve Knowledge Bases

Software doesn’t understand the nuances of language like we do. That’s why we’re often disappointed with responses from search engines. Sometimes they’re just not specific enough to help us. Other times, they lead us down a rabbit hole of irrelevant information that doesn’t answer what we want to know at all. That’s where natural language processing (NLP) comes in. In its most basic form, NLP makes software more human-like by allowing it to understand and respond to the way humans actually speak—the grammar, the slang, and so on. It makes it easier for people to interact with devices without having to use specific commands—like “Hey Siri” or “Okay Google.” The technology is rapidly improving as well, enabling more complex interactions between humans and machines without having to be so literal in our speech patterns. This is important because it means computers can better understand our needs in order to provide relevant answers and actionable information that actually helps solve human problems.

Korra’s Approach to AI Knowledge Bases Are the Future

Businesses know that maintaining an accurate knowledge base is important for their success. However, keeping them up to date is often a very time consuming, manual process. With Cognility, this problem is finally going to be solved; AI will do most of the work for you, without requiring a team of data entry people to keep your knowledge base relevant and up-to-date. Our technology is the future of insight engines, providing direct answers based on content within documents like PDFs, videos, audio tracks, and more. Find the answer you’re looking for in seconds using natural language input, the power of AI, and propriety SaaS technology found nowhere else.

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