Searchable knowledge base: How to make one, top tools, & more

A searchable knowledge base is a structured information hub, like Frequently Asked Questions (FAQs) or guides, built for quick and easy retrieval. It works by indexing content and using algorithms like typo-tolerant search to deliver precise results instantly.

Some benefits include slashing the volume of support tickets and boosting customer loyalty by proxy of independence. Common knowledge base types can be internal, for employee resources, and external, for customer help centers.

In this post, we’ll show you a couple of top tools for building a searchable knowledge base, and we’ll also show you how to build one using our own platform, Meilisearch. So, let’s get started.

What is a searchable knowledge base?

A searchable knowledge base is a structured repository or database of information, such as articles, FAQs, or guides, designed for effortless search and retrieval. Picture a digital library where answers to your questions are just one search away.

Unlike static or poorly organized knowledge bases that force users to manually sift through documents, a searchable system uses indexing, search algorithms, and metadata to deliver precise results amazingly fast. This ensures that users – whether customers or employees – find what they need without frustration.

First, let’s explore how these systems actually function.

How does a searchable knowledge base work?

A searchable knowledge base delivers answers with speed and precision by virtue of how it is built.

Here’s how it works:

• Step 1: Indexing refers to mapping out content, such as articles or FAQ pages, so the search engine knows exactly where to look. This process breaks down text into searchable components, making the search process fast.
• Step 2: When a user enters a query, algorithms scan the index produced in Step 1 to find matches. They rank results based on relevance, using metrics like keyword frequency or proximity. Tools like Meilisearch enhance this with typo tolerance, catching misspellings for better accuracy.
• Step 3: Metadata like meta tags, subcategories, or dates adds context to enable result filtering. For example, searching “billing issues” can be narrowed to articles tagged “invoices.” Faceted search, also supported by Meilisearch, allows users to refine results by specific attributes.
• Step 4: If all goes well, the search engine produces accurate and relevant results, often with highlighted keywords or snippets. For example, a query for “reset password” will pull up the exact guide instantly, saving users from manual browsing.

This process ensures users get answers quickly, which brings us to the tangible benefits.

What are the benefits of searchable knowledge bases?

Searchable knowledge bases help organizations manage information and deliver measurable advantages for users and intra-company teams.

Here’s why they’re a game-changer.

Improved user self-service success

Empowering users to find answers independently is a cornerstone of modern customer support. A searchable knowledge base lets customers resolve issues without contacting company support, increasing customer independence.

According to the Zendesk Customer Experience Trends Report 2020, 69% of buyers prefer to solve problems independently. Thus, such a self-serve model fosters user confidence and cuts down on repetitive inquiries.

Increased operational efficiency

Knowledge bases free customer support teams from answering routine questions by enabling self-service in customer support.

Gorgias reports that a well-implemented AI-powered knowledge base can decrease the ticket-to-order ratio by up to 27%. Reducing support agent contacts allows staff to focus on complex issues, streamlining operations, and reducing roadblocks to project progression.

Enhanced customer satisfaction

Quick access to solutions is a market-respected way to keep customers happy. A searchable knowledge base delivers answers in milliseconds, reducing wait times and frustration.

Research by Deloitte reported that brands that incorporate personalization into their customer service, an aspect that searchable knowledge bases facilitate, are 71% more likely to experience customer loyalty.

Better internal knowledge management

Internally, a searchable knowledge base centralizes critical information, from policies to troubleshooting guides. This reduces knowledge silos, ensuring teams stay aligned and the decision-making individuals stay informed.

Employees can quickly access up-to-date resources, improving inter-departmental collaboration.

These benefits vary depending on the knowledge base you implement, so let’s break down the different types.

What are the different types of knowledge bases?

Knowledge bases are versatile and can be tailored to serve specific audiences, purposes, and use cases. Understanding the types helps you choose the right one for your needs.

Internal knowledge base

An internal knowledge base is designed with a company’s employees in mind.

It usually houses resources like onboarding guides, standard operating procedures (SOPs), and troubleshooting FAQs. It streamlines knowledge sharing and typically uses enterprise search, ensuring team members have instant access to the information they need to excel in their roles.

External knowledge base

External knowledge bases, on the other hand, are more customer-facing and include FAQ sections, help centers, and support articles.

They empower users to find answers independently without ringing the help desk. By providing accessible, clear information, they reduce support inquiries and enhance the customer experience.

Product knowledge base

As the name suggests, a product knowledge base is focused on product-specific documentation.

It features developer docs, tutorials, and user guides. Customers and internal teams rely on this to use and support a product.

IT knowledge base

An IT knowledge base keeps IT teams happy and stocked with the information they need, when they need it.

It provides system information, troubleshooting guides, and network documentation. It serves as internal support, enabling IT staff to resolve technical issues efficiently and reduce system downtime.

HR knowledge base

An HR knowledge base not only keeps employees informed about their rights in the company but also lightens the HR team's workload.

It stores company policies, employee benefits, and compliance documents. Employees get easy access to resources like vacation policies or handbooks, thus promoting transparency and ensuring compliance across the organization.

What are the key features of an effective searchable knowledge base?

A functional, searchable knowledge base needs the following to ensure usability, security, and relevance.

Advanced search functionality

Robust search capabilities are non-negotiable for effective search. Features like typo tolerance, ranking rules, and faceted search make finding relevant information intuitive.

For example, Meilisearch’s typo tolerance ensures users get correct results even with misspellings, e.g., “invices” instead of “invoices”. Similarly, faceted search lets them filter by categories like “billing” or “technical.”

Real-time content updates

Keeping content up-to-date is vital for the most accurate results. Real-time updates, whether through versioning or live update systems, ensure users always have access to the latest information. This eliminates reliance on outdated guides, ensuring accuracy and establishing trust.

User-friendly content organization

Logical and user-focused content organization enhances usability. Intuitive menus and effective tagging help users navigate knowledge bases effortlessly.

Additionally, clear categories, such as “Getting Started” or “Troubleshooting” for product documentation, further improve user navigation in the answer-finding process.

Access control and permissions

Controlling access and permissions is essential, especially for internal knowledge bases. Defining access levels progressively up the organizational hierarchy ensures the right decisions are made at the right level.

Similarly, user-role-defined permissions ensure sensitive or department-specific content is only visible to authorized users. Together, access and permission controls protect data integrity and confidentiality.

Analytics and feedback mechanisms

Understanding user behavior is key to system improvement. Studying user analytics may reveal popular searches, content gaps, and where the search process leaves them wanting more.

Furthermore, feedback tools like “Was this helpful?” buttons help refine articles by identifying potential areas of improvement. This data-driven approach keeps the knowledge base relevant.

Mobile accessibility

In the age of mobile first, a knowledge base should be available on hand-held devices such as smartphones and tablets. Through responsive design, users can search and access information anywhere, increasing convenience and accessibility.

Next, let’s look at the best tools to bring these features to life.

What are the best software tools for building a searchable knowledge base?

The right tool depends on your organization’s size, needs, and technical capabilities. Here are the top five options to help you make that choice.

1. Meilisearch

Source: Meilisearch

Meilisearch is both an open-source and premium search engine that delivers lightning-fast, relevant search experiences. With search-as-you-type results in under 50 milliseconds, typo tolerance, and hybrid search combining keyword and semantic capabilities, it’s perfect for building intuitive knowledge bases. Plus, its plug-and-play setup, RAG-based infrastructure, and SDKs make integration into virtually any infrastructure a breeze.

Best for: Organizations seeking a user-friendly, scalable, and intelligent search solution.

2. Atlassian Confluence

Source: Atlassian Confluence

Atlassian Confluence is a collaborative platform built specifically for creating and managing internal knowledge bases. It offers real-time editing, version control, whiteboards, and robust search functionalities.

It also comes equipped with templates for organizing content. One of its defining features is seamless integration with Jira, Slack, and many other tools, making it ideal for teams within and outside the Atlassian ecosystem.

Best for: Teams needing a collaborative, enterprise-grade documentation platform.

3. Zendesk

Source: Zendesk

Zendesk’s help center software includes a powerful knowledge base for customer self-service. It artfully combines generative and agentic AI with content management and user analytics to reduce ticket volume by up to 15%.

Plus, its intuitive interface and reporting tools make it a strong choice for support-focused organizations.

Best for: Businesses wanting an integrated customer support and knowledge base solution.

4. Helpjuice

Source: Helpjuice

Helpjuice is another user-friendly inter-team knowledge base platform with AI-assisted content creation and typo-tolerant search. It offers rich formatting for easy content creation within the platform, multi-language support for truly global teams, and analytics to track user behavior.

Its AI-powered chatbot and search functionality, coupled with multiple customization options, make it ideal for global teams needing tailored solutions.

Best for: Companies prioritizing ease of use and advanced content management.

5. Notion

Source: Notion

Notion is a versatile workspace combining wikis, documentation, and project management. Its flexible infrastructure, powerful search capabilities, and AI features make it great for creating all kinds of knowledge bases.

It has remarkable security features, while teamspaces and integrations enhance collaboration across tools.

Best for: Teams wanting an all-in-one platform for knowledge and project management.

Now, let’s dive into building a knowledge base with Meilisearch.

How to create a searchable knowledge base with Meilisearch?

Meilisearch transforms a basic knowledge base into a superior searchable experience with speed, accuracy, and relevance.

Here’s a step-by-step guide to get you started.

1. Set up Meilisearch

Getting started with Meilisearch is a breeze. Choose Meilisearch Cloud for a managed, hassle-free setup, or self-host using Docker, a binary, or other methods.

For self-hosting, install with a command like:

# Install Meilisearch
curl -L https://install.meilisearch.com | sh

Secure your instance with API keys (master, admin, search) to control access and permission levels, maintaining a tight grip on your knowledge base’s protection.

2. Create an index

An index is Meilisearch’s container for your searchable documents, like articles or FAQs. Create one via the web UI or API, naming it something relevant, such as “knowledge-base.”

This organizes your content, setting the stage for efficient searches. Here, a REST API call like POST /indexes with {"uid": "knowledge-base"} would do the trick.

3. Add documents

Populate your index with content formatted as JSON, NDJSON, or CSV files. Make sure to assign a unique identifier (e.g., “id”) to each document. Use the web UI for small datasets or the REST API/SDKs for bulk uploads.

Here’s a Python script example:

# In the command line:
# pip3 install meilisearch

# In your .py file:
import meilisearch
import json

client = meilisearch.Client('http://localhost:7700', 'your_master_key')

json_file = open('knowledge_base.json', encoding='utf-8')
documents = json.load(json_file)


json_file = open('knowledge_base.json', encoding='utf-8')
documents = json.load(json_file)


client.index('knowledge-base').add_documents(documents)

This code assumes you have a knowledge_base.json file with content like this:

[  {
    "id": 1,
    "title": "How to Reset Password",
    "content": "Step-by-step guide to reset your password."
  },
  {
    "id": 2,
    "title": "Account Settings",
    "content": "Manage your account preferences."
  }
]

Save this JSON in knowledge_base.json, and the code will upload it to the knowledge-base index.

4. Configure search settings

Customize how searches work by defining searchable attributes (e.g., “title,” “content”) and ranking rules to prioritize results, like favoring recent or relevant documents.

Enable filters and facets for users to narrow results by categories or dates. For instance, set searchable attributes via the API: POST /indexes/knowledge-base/settings with {"searchableAttributes": ["title", "content"]}.

5. Integrate search into your application

Bring search into your app using Meilisearch’s REST API or SDKs (Node.js, Python, etc.). Query the index from a search bar and display results with highlighted matches.

Here’s a JavaScript example:

const { MeiliSearch } = require('meilisearch');
const client = new MeiliSearch({ host: 'http://localhost:7700' });
client.index('knowledge-base').search('reset password').then((results) => {
    console.log(results.hits);
});

This retrieves and logs search results, ready for display.

6. Advanced features

Meilisearch’s advanced features elevate your knowledge base and take it from what it is to what it can be.

Typo tolerance ensures that accurate results appear despite misspellings, while synonyms and stop words improve relevance by handling related terms or ignoring common words. Hybrid search blends keyword and semantic search for context-aware results, ideal for complex queries.

And you can configure and optimize these via the API to fine-tune your search experience.

With these steps, your knowledge base is ready to shine!

Over to You!

A searchable knowledge base empowers users and simplifies information access across platforms quickly. Meilisearch enables you to create a fast, intuitive system tailored to your organization's requirements, whether for customer support, internal documentation, or product documentation.

This helps reduce support tickets, improve efficiency, and boost customer satisfaction, giving your company a strategic advantage. Start now and find out how Meilisearch enables your users to find answers.