What Is a Knowledge Base?

What Is a Knowledge Base?

A knowledge base can be an organized repository of information, written articles, FAQs, product documentation, troubleshooting steps, policies, and guidelines – to name a few. This information can then be organized into a self-service resource for your business.

Knowledge bases are typically implemented as self-service resources. Instead of having to contact someone every time a question arises, users can look up the answers to their questions in the knowledge base themselves. The target audience for a knowledge base can consist of external users (such as customers) or of internal users (such as employees and support staff).

A Knowledge Base can be a simple accumulation of Help Articles or even a sophisticated system that uses AI to understand natural language questions and provides the best possible answer by searching multiple sources of knowledge.

How Does a Knowledge Base Work?

A knowledge base usually starts with the collection of relevant information, organized in a specific structure to create a repository of knowledge. This information can include product documentation, FAQs, how-to articles, internal processes, technical guides and more.

In a Knowledge Base, the information that has been stored is then used to provide answers to a user’s questions. Users can search for the information they require using a variety of methods including search facilities, categorization, menus and hyperlinks.

If information is well-organized and is clearly written, retrieval of information in a knowledge base is good. Information that is most requested should be easily accessible. Information in the knowledge base should remain consistent.

Collecting and Organizing Information

First the relevant information must be collected from sources such as help topics, FAQs, support articles, company policies and other documents. Then this information is grouped by topics, products, departments, user groups or even types of questions.

Organization of the knowledge gathered is important, because it reduces the time spent by users searching for information and makes it easier for teams to update specific parts of the knowledge base as products, processes and policies evolve.

Storing Knowledge in a Central Repository

A knowledge base provides information in a central location – unlike information scattered across emails, documents, support requests, etc.. Central storage of information means that users can always refer to the same source of information, thus avoiding discrepancies between teams.

Searching and Retrieving Information

Typically, the user searches for information using the search function provided or simply browses the knowledge base by category. Most Knowledge Bases are based on simple keyword matching to return the most relevant information for a question. However, modern Knowledge Bases utilize semantic search so they can actually understand a question asked in a natural language form and return the most relevant and related information.

Delivering Relevant Answers

Finally, once information has been located, the knowledge base presents this information to users. The information can be a complete article, or just a section of a document, or even a generated answer based on more than one piece of knowledge.

What Is an AI Knowledge Base?

An AI knowledge base is a combination of a classical knowledge base and AI technologies. Instead of reading one article after another, the user can enter a question in natural language, and the AI knowledge base searches the knowledge base for relevant content.

The application of AI in a knowledge base often involves Natural Language Processing (NLP), semantic search, document embeddings, and Retrieval-Augmented Generation (RAG) for connecting user queries with relevant content even when there is no word match between the user query and source material.

AI knowledge bases are particularly powerful for very large amounts of documentation, where search manually would fail.

How Does an AI Knowledge Base Work?

The information is processed prior to retrieval. Each document or information source is divided up into the individual sections and these are converted into numerical embeddings that allow for determination of relationships between the meaning of a user’s query and the information in the knowledge base that has been added by others.

When a question is asked by a user, the system analyzes the input query and uses it to search for relevant information in the Knowledge Base to provide answers to user questions. That information is then used by a generative model to generate answers.

Semantic Search and Embeddings

The search is semantic, and not restricted to an exact word search. The embeddings allow for a comparison of the semantic space between the query and the information in the knowledge base.

This is what allows an AI Knowledge Base to search for information even when the user has not expressed themselves in exactly the same words as the writer of the source documents.

Retrieval-Augmented Generation (RAG)

Retrieval-Augmented Generation (RAG) is a type of application that pairs information retrieval with a generative model. This model generates an answer by using the retrieved information for the question asked. In the case of the knowledge base, this answer is grounded in the information provided by the organization.

Since the answer is generated based on the retrieved information, RAG enables AI systems to provide answers that are grounded in an organization’s documentation, rather than relying on the information that the AI system learned during its own training.

Generating Grounded Answers

A knowledge base can be used to generate answers in natural language. These answers are summarized from the information that was found in the knowledge base and thus provide direct answers to questions posed to an AI system.

Note, however, that the reliability of generated answers greatly depends on the quality, accuracy and up-to-dateness of the stored knowledge.

What Types of Information Can a Knowledge Base Store?

Content in a knowledge base is often structured (e.g. FAQs, procedures) or unstructured (e.g. manuals, blogs) and depends on the organization and the intended use of the knowledge base.

Information to be stored in the Knowledge Base of an AI Knowledge Base includes frequently asked questions, product documentation, user manuals, troubleshooting instructions, technical documentation, company policies, and much more.

For customer support, knowledge bases that are integrated with support tickets, customer service chats and other relevant systems are used to document solutions to common problems. Customers can use self-service to find answers to their questions and reduce the volume of repeat issues that need to be dealt with by support agents.

What Are the Benefits of a Knowledge Base?

A knowledge base is typically viewed as a means to enable users of greater access to information and thus greater self-service than would be the case were they forced to depend on another human for answers to their questions.

A knowledge base can also support customer service, by enabling customers to solve common problems themselves. The repetitive questions that support staff have to deal with can be significantly reduced, allowing them to focus on more complex issues and help customers with more complex problems.

Knowledge bases are especially useful internally to a company for disseminating organizational knowledge and information regarding procedures, policies, technical information and training. Users can easily find and access information previously dispersed throughout multiple systems.

Consistency: Because teams use a single source of information, customers and employees will consistently receive accurate and consistent answers and instructions.

Knowledge Base vs. AI Knowledge Base

A traditional knowledge base is used to search for information, whereas an AI knowledge base is able to read a question, search for relevant information and then generate an answer from that information.

What Are the Applications of a Knowledge Base?

Knowledge bases are applied in many areas of application where information is required in a reliable manner.

Customer Support: Answers to frequently asked questions, product information, troubleshooting, account and billing information etc. Customers can search for answers in a help center or interact with an AI-powered assistant to get immediate answers.

Employee support: Organize HR information such as employee policies and benefits, as well as information to help new employees through onboarding. Employees can then search for the information they need as opposed to having to call different departments with routine questions.

IT help desks often maintain knowledge bases detailing the solutions to common problems. This may include information on how to install software, how to access accounts, how to configure computers, how to fix problems with the network, and more, in the form of step-by-step procedures that employees can refer to or that the help desk uses to service client calls.

Product support knowledge bases contain the product manuals, setup guides, feature documentation and FAQs for customers and users of a software product. The number of features in software products has increased greatly in recent years and the frequency of updates to existing products has also increased greatly.

For Sales and Customer Success, a knowledge base contains information on products, pricing, implementation, FAQs and more. Teams can quickly reference this information to best serve their customers.