With ‘intelligence’ everywhere, why should ‘search’ miss out?




Wissen Team


July 2, 2024

Most industries today are well-aware of the potential benefits of technologies such as Artificial Intelligence and Machine Learning. 

As the digital transformation drive increases across industries, more organizations look towards modernizing their operations, ‘Intelligent Search’ is fast emerging as a business necessity.

What is intelligent search?

Almost 80% of all enterprise data is unstructured and scattered in emails, text documents, social media posts, queries, customer reviews, support requests, and images. Most of this data contains valuable information that needs fast and easy access. However, the traditional search tools are keyword dependent and cannot discover relevant information in the ever-increasing unstructured data.

This challenge can be solved using Natural Language Processing (NLP). NLP, an AI technique that translates human communication to make it coherent to a computer in the same way that it would be to another human, enables us to deliver Intelligent Search. 

Intelligent Search can be considered the next generation of enterprise search. Instead of relying on simple statistics or keywords, Intelligent Search uses AI and ML to help people improve their search accuracy and makes the search more cognitive.

With only keywords, it is challenging to find meaning inherent in a query, and the precision yield of such results is low. But AI changes the search game and makes the search more ‘intelligent’ by facilitating the understanding of grammatical and ungrammatical questions as well as understanding period queries.

Benefits of intelligent search

Using Intelligent Search allows enterprise users to:

  • Conduct targeted search and perform paragraph-level scoring
  • Identify events and relations to unstructured data and convert it into triples form
  • Filter documents faster and with more accuracy based on time expressions in the query
  • Get high-quality search results even with grammatically incorrect queries
  • Get exact data from document tables
  • Identify semantically and syntactically similar tokens and entities automatically
  • Perform searches on ontological entities using domain-specific knowledge graphs

Organizations can leverage advanced cognitive search features to comprehend human language and extract meaningful information across any knowledge base. 

Intelligent Search facilities deeper comprehension of search and semantics that helps users discover the relevant data necessary to improve their business intelligence.

Introducing wissen’s intelligent search accelerator 

Machine Learning and Artificial Intelligence should be use-case specific for these investments to deliver an RoI. However, developing a solution internally can be an uphill task for reasons such as lack of domain knowledge, technical expertise, and modern solution-designing experience. 

Good to use, plug-and-play solutions are the ideal choice in this case.

To assuage this challenge, we have used our domain, technological and solutions expertise and developed an ML-based accelerator that helps enterprises leverage the benefits of Intelligent Search. 

Using this accelerator, organizations can discover documents specific to a topic and pinpoint the most relevant paragraph for a given query.

Our Intelligent Search accelerator is powered by NLP, Semantic search, and ML techniques and provides semantic information from documents. It also conducts the ‘search’ function by putting the ‘context’ of the question to work. 

Using Wissen’s Intelligent Search accelerator, organizations can – 

  • Easily scan through large and voluminous reports and get the most relevant results for questions
  • Gain robust and extensive text pre-processing capabilities to produce a deeply enriched version of the input. It also converts unstructured data from free-form text, HTML documents, images, and tables into intermediate form and stores it as triples
  • Leverage lexical analysis, linguistic and semantic analysis on documents and queries, and paragraph relevance scoring for relevant search output
  • Boost relevance score by employing hierarchical properties of the document text
  • Link unstructured data with both internal and external structured data to drive powerful analysis
  • Get exact data from document tables even if the document is an image
  • Access context-aware entity extraction

Key features of the intelligent search accelerator

Some of the key features include- 

  • Ability to easily integrate with the organization’s Contract Management Systems and capably scan legal documents for specific clauses 
  • Easy integration with a chatbot search to generate a relevant history of data already present on the website
  • High scalability and ability to be integrated on the cloud and scaled dynamically with ease 
  • No dependency on manually labeled data in the accelerator 
  • Seamless integration with the client’s infrastructure (both on-premise and cloud)

The accelerator has been developed and designed keeping in mind the imperatives of engineering that go into designing highly scalable digital solutions. Our expertise in working with unstructured and semi-structured data from multiple sources and formats and our domain and technology expertise has ensured that this solution can be implemented enterprise-wide on the latest technology stack.

If you feel your organization could benefit from adding ‘intelligence’ to the ‘search’ functionality, connect with us at hello@wissen.com