How Intelligent Search Works and its Evolution Over Time

What is an intelligent search? Intelligent search is technology supported by artificial intelligence to help remove data silos and assists employees and consumers in quickly finding the information they require. End users may use intelligent search to extract information from everywhere and in any format, be it from databases, document management systems, digital content, webpages, papers, and many more. Natural language search, AI search or AI-powered search, and cognitive search are all synonyms to intelligent search and enterprise search.


The Evolution of Intelligent Search


Enterprise information retrieval systems existed far before the public internet. One of the first advantages of deploying multi-user mainframe computer systems was that they aided in discovering perfect matches to text strings in massive document libraries.


With time, commercial business search solutions became the standard in enterprise computing as desktop computing and corporate intranets grew in popularity.


However, the development and popularity of free, publicly available online search engines like Google (and its precursor AltaVista) changed consumer expectations for information retrieval, content discovery, and business search platforms.


With the volume and diversity of data that business search tools must evaluate rapidly increasing, the speed with which results are returned has emerged as a crucial indicator of the effectiveness of cognitive search algorithms. Today's intelligent search solutions need to be developed on architectures capable of handling the performance needs of huge data workloads. Cloud infrastructures with substantial API-driven interfaces and automation are typically best suited for the work since they provide the required scalability.


Traditional Search Engines Versus Intelligent Search Engines


Businesses cannot use standard search engines to fetch answers to questions like "why is our new product shipping delayed?" or "What were our most frequently reported consumer issues last week?" Unlike search engines and online search, intelligent search reveals information and answers unique to your organization.


Intelligent search is powered by artificial intelligence, which gives tools the capacity to:



• Recognize human language. Business data is updated regularly and provided in domain-specific terms. Intelligent search software can analyze and query digital material from many data sources thanks to natural language processing capabilities. Intelligent search can use semantic search and contextual knowledge to break down linguistic subtleties, synonyms, and relationships present in common language and inside complicated publications.

• Understand the structure of documents. Intelligent search systems include a document comprehension AI that is scalable to grasp a wide range of data sources. Intelligent search can use machine learning to understand the visual layout of documents particular to your company, industry, or domain-space. Using this understanding, it can learn and detect items like headers, charts, footers, and tables. It can recognize document types such as contracts, purchase orders, and invoices right out of the box.



• Make use of machine learning. Machine learning and deep learning generate seamless, instant query recommendations and constantly enhance search query result relevancy over time, predicting what information would be most useful to consumers.

• Filter results after searching. Faceted and filtered searches restrict the scope of data types and help uncover specific information that can be critical in the decision-making process.

• Classify and categorize data. Entity extraction finds and categorizes text data items such as names of people, products, object types, and so on.


How Intelligent Search Works?



Connect data sources and ingest data: In order to retrieve answers and insights, you must allow intelligent search to connect and crawl all of your unstructured and structured data. A "connector" allows you to connect to a content source like Salesforce, Microsoft SharePoint, Box, Web Crawler, Databases, or Uploaded data.



Index content: Content indexing produces a single unified search index that allows search results to be ranked homogeneously regardless of their source.

Enhance content: The capacity to query and extract insights from your material is based on the ability to extract metadata from your content. Use out-of-the-box natural language processing enrichments like entity extraction and sentiment analysis to categorize and find essential material to enhance your content. 

Analyze content: Recognizes document contents, categorizes them, and generates semantic relationships between individual bits of material.

Provides insights and responses: Intelligent scoring algorithms rank texts and return to users the most correct, relevant passages and snippets as an answer to their query.


Intelligent Search Query Examples


Intelligent search matches phrases in natural language searches to material in its indexed data. For example:



   • Questions: "How many vacation days am I allowed to take?"

   • Statements: "I am applying for a mortgage," 

   • Keywords: "Health Insurance rates" is a keyword.


Benefits of Intelligent Search



Provides insights to guide decision-making: Your unstructured text data has insights. To expose real-time insights with speed and precision, intelligent search apps utilize natural language processing to extract meaning and find connections across data sources like social media, customer feedback, e-commerce reports, and maintenance records.

Puts vital information at the hands of your employees: To provide employees with a simple and convenient team-wide user experience, use intelligent search to create an enterprise search platform, knowledge management, content management system, or question answering system.

Provides scalable customer service: One of the benefits of intelligent search is giving customers the correct response they need, which helps improve customer experience and satisfaction. Customers want more than just FAQs. They want to self-serve on your websites and mobile applications now more than ever, and the only thing that can enable your customers attain independence is virtual agents and intelligent search. Customers who are self-sufficient result in lower support costs and increased customer satisfaction.


Case Studies


Businesses save documents and data in both unstructured and organized formats across many sources. Employees spend an average of three hours every weekday looking for information.


Finding insights and resources within your organization's unstructured data should be straightforward. It is time for your company to get data driven with intelligent search. 

     • It saves time. Banks could automate knowledge discovery such that 10 days of labor could be completed in two minutes.

     • Saves money. An energy customer saved up to USD 10 million in time by reducing time spent searching for relevant information inside their organizational knowledge bases. 

     • Less workload. An insurance customer decreased the effort of reading and analyzing internal corporate data by 90%. 

     • Increases revenue. Law companies employ search software to streamline business operations and become four times more efficient, resulting in up to a 30% increase in income.

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