Knowledge Base

What is a Knowledge Base?

A knowledge base is a self-service resource providing information about a company’s products or services. Information can range from product descriptions and instructions to the workings of different company departments. The data within your knowledge base could come from anywhere, including internal and external resources. It would typically be expanded by those well-versed in the subject matter, such as products, services or topics.

What is a Knowledge Base in Artificial Intelligence?

Artificial Intelligence (AI) can be used to simplify the process of searching a knowledge base. Using keywords and phrases, AI can quickly find the answer or solution by scanning multiple types of information, improving the knowledge intelligence of your knowledge base. Knowledge bases in AI can also unify siloed information sources into one centralized library, meaning that people can quickly search for and receive the information they need, without going from department to department.

Components of a Knowledge Base

A knowledge base is typically comprised of multiple components. So it’s worthwhile to take the time to understand how knowledge bases work before implementing one into your business.


An ontology is a data model that defines the types of things within a database, their properties and interrelationships. As an ontology is a general data model, it only describes broad concepts and shared properties. It doesn’t include more specific information on individual items within a knowledge base.


A taxonomy is a categorization scheme of information into different categories and subcategories. Taxonomies use clear categories and tags to make information easily searchable. If the tags are broad or vague, they are less likely to add value. The tags used in a taxonomy should create a balanced view of the information as a whole.


Instances are an object belonging to a certain class or category. Instances within a class might share the same set of attributes, but what comprises an attribute is where they could differ. For example, two products may both have the same attributes, e.g. product name, year of release, and product type. However, what those attributes contain will be different as they relate to each product.


Instances in a knowledge base don’t exist in isolation. Rather, there are connections between them called relationships. Relationships describe associations between different instances. For example, there would likely be a relationship between customer information and order data.

What Are the Types of Knowledge Base in AI

Knowledge bases can have different ways of organizing and representing information. It’s important to consider which one would suit your knowledge base.

Rule-Based Systems

A rule-based system represents the information within a knowledge base as a set of rules. It outlines triggers, which is the condition that sets a process in motion, and the action that should then follow the trigger. It’s important to ensure rules are written accurately, as the AI will follow whatever it’s dictated to do.

Frame-Based Systems

Frame-based systems use frames to divide knowledge by representing concepts or situations. Attributes are attached to the frame in slots. These attributes include how to use the frame, what the expectations are, and what to do when the expectations aren’t met.

Model-Based Systems

Model-based systems use working models combined with real-world observations to draw conclusions. Knowledge is built into the model so that it can return a result when it is interacted with. They can be used to test hypotheses or send alerts when certain information is inputted.

Description Logic Systems

Description logic systems describe knowledge in terms of classes, properties, relationships and individuals. A description logic system at a basic level consists of a concept and a relationship. Description logic systems also use formal, logic-based semantics to describe the properties and relationships between different concepts.

Industries that Use a Knowledge Base

Knowledge bases are useful for a variety of industries, as they can help centralize information and assist employees. Some of these industries include:

  •   Financial Services. Banks and other financial institutions can benefit from a knowledge base that details compliance practices. This knowledge base could contain all the information employees would need to ensure they follow procedures and policies correctly.
  •   Healthcare. Like in the finance industry, the healthcare industry has rigorous regulations to follow, and there is also the added pressure of how harmful mistakes can be for patients. A knowledge base can act as a guide and a single source of truth for employees.
  •   Customer Service. Customer service agents must be able to provide customers with the correct information quickly. Knowledge bases make this possible, providing an easy source of information for employees to search and find the correct information.

Pros of a Knowledge Base

Knowledge bases offer the opportunity to bring all business information together in one place, which brings several benefits.

Improved Efficiency

A knowledge base can act as a one-stop shop for information for employees. This means rather than spending time searching around, they can quickly get the correct information and take the right action, speeding up processes.

Better Customer Service

A knowledge base can benefit customer service processes by allowing agents to find relevant information quickly – whether that’s searching for the correct purchase information or finding pertinent product or maintenance information to help solve a customer’s query.

Improved Data Organization

Disparate data only leads to breakdowns and inefficiencies further down the line. Unifying information into one centralized hub allows all relevant internal and external company information to be found quickly and easily.

Cons of a Knowledge Base

Knowledge bases can also have some drawbacks in their adoption and maintenance, which are important to consider when you’re thinking about implementing one.

Risk of Human Bias

Knowledge bases begin as empty databases and are built up from information that is inputted into it. This means building a full picture of all relevant information is important. If those building it out input more information on certain departments or categories, the information within the knowledge base can be imbalanced.

Scalability Challenges

Growing the knowledge base is a time-consuming and long process, and as your company grows, your knowledge base must do the same. This can mean spending more money and resources investing in a knowledge base solution that has the scalability your company needs. Without it, your knowledge base can become futile, unable to keep up with increasing amounts of data and information.

Potential for Ambiguity and Incompleteness

Due to the constantly changing nature of business processes and policies, your knowledge base is never complete. As your procedures change, the knowledge base needs to be updated with this. It is considered best practice to have at least one person responsible for keeping the knowledge base updated with accurate information.

How Do You Create a Knowledge Base in AI

Creating a knowledge base in AI is often done in one of two ways:

  •   Implementing AI into an existing knowledge base. AI can be integrated into an active knowledge base. This includes using chatbots to respond to customer service questions, machine learning (ML) to make recommendations to employees, or natural language processing (NLP) to analyze correspondence for relevant information.
  •   Implementing a new AI-based knowledge base. Rather than working with an existing system, this option means starting from scratch with a knowledge base with AI capabilities. Whilst it may take longer, it may yield better results as the new knowledge base can be purposefully built instead of a workaround.

The Future of Knowledge Bases

As the capabilities of AI grow, knowledge bases will only become more useful. Especially in the future of customer care, through chatbots or live assistance in customer interactions, the partnership of AI and knowledge bases enables employees to access information quicker, sometimes before they may have realized they need it. In this way, knowledge bases can become a part of human augmentation. What is human augmentation? It is the improvement of human capabilities through technology, which knowledge bases accomplish by improving employee efficiency and customer service skills.

Even more generally than this, the amount of information and data out there is only growing, and it’s only to your benefit if you can make this accessible and searchable. By using a knowledge base with AI, you empower your business with a strong information center and offer an easy way for your employees to keep up with changing processes or data.

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