What Is Intelligent Search and How Does It Work?

Information truly is the key to success, but as keys tend to do, they get lost in a mess. A report by McKinsey found that workers spend about 20% of their workweek simply searching for internal information or looking for colleagues who have the answers to their questions.

For companies of any size, this can lead to unproductivity of employees. In fact, this wasted time can even translate into revenue loss for businesses that aren’t actively keeping a watch on it. Fortunately, there’s a solution to this problem, and it’s called Intelligent Search.

What Is Intelligent Search?

Alt text: Illustration of a robot standing behind a search bar, appearing to offer assistance.

Intelligent search is arguably a step ahead of traditional search. Traditional search works by a user feeding it a keyword, based on which its algorithm puts forth countless results that match the provided keyword. While this works, it's not the most efficient, and it certainly takes up more time than it should have.

Intelligent search goes beyond a simple keyword-matching process, looking into the nooks and crannies of the user’s search query and understanding their potential intent, context, and meaning behind the posed question to provide relevant results accurately and quickly.

For example, say you’re planning a trip to Paris and type into a traditional search engine “Paris trip.” It will focus on the provided keywords and provide you with thousands of results that include the exact match keyword. However, the results could vary from blog posts, travel guides, any books with that name, images of the Eiffel Tower, and more. It’s like a ball of randomness that only “hopes” for the desired results.

On the other hand, intelligent search reads into your search intent, understanding you’re planning a trip to Paris, and provides results that are relevant and useful, such as the best time to travel, budget, things to do, and more. If you provide more information or answer a follow-up question, more focused results and even personal recommendations like highly rated hotels, restaurants, and attractions will pop up.

Here are some core features of an intelligent search:

• Natural Language Processing (NLP): Natural Language Processing enables it to understand and interpret human language as it is spoken or written, including slang, synonyms, and context. As the name might suggest, search engines using NLP can be conversed with in your everyday language, making them extremely user-friendly, and they simply feel “more natural.” This feature is crucial for integrating AI into your business, allowing for a more intuitive interaction with data.
• Machine Learning (ML): A subset of artificial intelligence (AI) that allows the system to learn from experience and adapt to new situations, much like humans do. This includes algorithm improvements, understanding patterns, and learning from feedback. This reflects AI's impact on business intelligence, enhancing data-driven decision-making.
• Semantic Search: Semantic search utilizes NLP and ML to understand the meaning behind words and phrases, taking into account the context of a search query and bringing in results that are more aligned with your intent.
• Personalization: Intelligent search personalizes results based on history, preferences, location, and behavior. This ensures your desired results are delivered much faster instead of trial and error.

How Does Intelligent Search Work?

The foundation of intelligent search is its ability to understand natural language, granted by NLP. AI is the broadest concept of the three, with ML being a subset of AI and NLP being an application of it. With that in mind, this combination has the ability to understand queries even when they include slang and synonyms, as well as taking into account the context and relationships between the words.

Now, how intelligent search actually works goes something like this:

1. Integration of Data Sources

As expected from a data source, the first step is to provide it with structured and unstructured data from all available sources. For example, databases (Microsoft Sharepoint, Salesforce), internal files, emails, and documents. The more data you feed into the intelligent search engine, the more thorough its database; leading to more accurate information. This process complements existing enterprise knowledge management systems, optimizing the way data is handled and utilized.

2. Index Content

For searching effortlessly across multiple data sources and maintaining relevancy, the creation and maintenance of a unified search index is done. The system here organizes unstructured and raw data, which makes the retrieval process much easier.

3. Enrichment of Content and its Analysis

NLP takes charge here and extracts any insights it can from the metadata, for example, entities and sentiment, for a deeper understanding and categorization of the data. This information, picked from various sources, is studied thoroughly and analyzed for correlations and any useful relationships between them.

4. Delivery

Unlike traditional search results, the intelligent search will dish out highly relevant results based on the user’s search query, understanding of context, and user intent. The information that the user is provided is further enhanced by the algorithm by adding some useful insights it is able to gather.

Benefits of Intelligent Search for Users

The huge volume of digital information can be overwhelming for any individual to deal with. On top of that, traditional methods of searching, relying on basics like keyword matching, are no longer efficient. In contrast, intelligent search enhances the search experience for users, more specifically, for employees of a company. Here are some of the many benefits of it:

• Provides Better Time Efficiency: Considering the various studies that point towards the amount of time employees spend looking for data, intelligent search can help reduce that significantly. By delivering precise results quickly, users can focus on more productive tasks.
• Understands Natural Language: The biggest benefit of intelligent search is its ability to feel almost like a know-it-all member of your team. You don’t have to formalize or phrase your question in a specific way; simply write it down in your natural speaking or writing tone. Irrespective of your format, the AI is able to understand your query, being endowed with the ability to understand synonyms, slang, and colloquial phrases. This ability leads to users utilizing the platform more as it feels a lot more responsive and interactive.
• Helps with Decision-Making: With the ease of access, accuracy, and responsiveness of intelligent search, users can make decisions quicker. Time is important, and in a fast-paced world, quick but informed decisions lead to a competitive edge.
• Increased Engagement: A platform that has intelligent search makes it more likely to be explored, considering how interactive the nature of this technology is. Employees are exposed to a wider range of relevant content that may have otherwise gone unnoticed. This capability also encourages a habit of self-service, where employees can find answers independently without overly relying on support teams.
• Constant improvement: As the name suggests, intelligent search is “intelligent” enough to understand user behavior, patterns, keywords, and ways of communication better with time. It constantly improves itself and provides improved results.

How Atlas UP Can Help with Intelligent Search

Alt text: A screenshot of Atlas UP’s homepage.

You can say goodbye to endless searching with Atlas UP, an AI knowledge base software that allows you to ask questions about your company data and get answers instantly. It’s designed to make finding information a breeze for your business. Being capable of intelligent search, it can siphon through your data, structured and unstructured, analyze it, break down knowledge silos, and give you the desired information.

Here’s how Atlas UP can help your business:

• Intelligent Search: Our AI-powered search understands what you’re looking for, even if you’re not sure how to ask. Just type in your question, and Atlas UP will deliver accurate results fast.
• Natural Language Processing (NLP): Atlas UP uses NLP to grasp the meaning behind your queries. This means you get the answers you need without going through irrelevant data.
• Unified Knowledge Base: Atlas UP pulls data from all your company’s sources into one easy-to-access place. No more jumping between systems to find what you need.
• Continuous Learning: The more you use Atlas UP, the smarter it gets. Our AI learns and adapts to your business, ensuring search results stay relevant as your company grows.
• Boost Productivity: With quick access to information, your team can spend less time searching and more time on what matters.

And that’s not all!

At Atlas UP, your data security is our top priority. We use cutting-edge data encryption and follow strict SOC 2 Type II and GDPR compliance. Your data stays yours. We never use it for model training or marketing without your permission.

Providing employees with the ability to instantly get an answer to any of their questions saves everyone time, eases many procedures, and builds a culture of curiosity and almost self-reliance of sorts. Of course, access to information can be adjusted as per requirements. Schedule a demo with us today to see the tool in action.

Closing Thoughts

Intelligent search is a fast, factually accurate, and efficient method of looking for information, all without the formalities of writing a proper email to a fellow teammate and waiting endlessly for their reply. Shifting to an AI-based search software can seem to be a major change, and it is, but the benefits are undeniable when traditional search methods are starting to feel inefficient. Atlas UP can fill the role, become your company’s knowledge base, provide valuable insights, improve workflows, and empower employees by providing them with the right information at the right time.

Frequently Asked Questions

What does intelligent search do?

Intelligent search is an AI-powered process that understands natural language, user intent, and the meaning behind a question to provide a more relevant answer as compared to a traditional keyword-based search method.

What is the difference between normal search and intelligent search?

Traditional search relies solely on keywords, which usually results in broader results. For example, searching for “Apple” would bring up both the fruit and the company. Intelligent search, however, is much more personalized, understands context and intent, and displays relevant results. It even delivers insights.

What is an intelligent search algorithm?

The intelligent search algorithm uses artificial intelligence, natural language processing, and machine learning to enhance search results. The algorithm, thanks to its core elements, is capable of understanding intent, learning from interactions, and providing contextually relevant results.