EnterpriseNLP - Natural Language Queries for the Enterprise


 Our natural language EnterpriseNLP  lets businesses quickly ask complex questions against millions of documents using simple english. Who is the ... Where can I find... What does ...

           10 to 100 millisecond response time
           Easily integrates into SOLR search engine
           Supports millions of documents
           Shows you the answer, not just a document link
           Award Winning Technology

Is your current enterprise search solution not really finding you the information you need? Tired of clicking page after page of documents never finding what you want?

EnterpriseNLP provides a more modern way to search using language analysis - natural language processing. Technically it is part of the new emerging field of Insight Engines and Natural Language Understanding - it goes far beyond simple indexing engines.

How EnterpriseNLP is different:
For real value add to the modern enterprise, traditional search is not enough. Leveraging enterprise scale natural language processing - cognitive search - is what Forrester Research has recognized as the next evolution of search. 

According to Forrester Research,  Cognitive search and knowledge discovery solutions should: 
  • Understand any data that enterprises can throw at it. First and foremost, cognitive search solutions must connect to and ingest data from a wide variety of sources. Search is no longer just about unstructured text contained in documents and web pages. 
  • Scale to handle big data. It is not uncommon for a large enterprise to have a portfolio of hundreds or sometimes thousands of applications, potentially reaching over a petabyte of data stored on-premises or in the cloud. All these applications generate data that is potentially valuable for search applications. 
  • Implement Ingestion Intelligence - We use several techniques at data ingestion time to increase the power of NLP search including typing of the query vs typing of the sentence, named entity recognition, and intent recognition.

According to Gartner, Natural Language Processing is a key technology companies will be adopting:
  • By 2020, 50 percent of analytical queries will be generated via search, natural language processing (NLP) or voice, or will be automatically generated. The need to analyze complex combinations of data to make analytics accessible to everyone in the organization will drive broader adoption.

Regular search systems just use the word frequency across the whole document. EnterpriseNLP uses grammatical analysis, morphological role,  and sentence dependency structure to show you the exact sentence that matches your query. It shows you the answer, not just a document link. 

        Support for special query types and named entity recognition: 
                  people  (Who is ...)
                  locations  (Where are ...)
                  date and time   (When is ...)
                  money   (How much does ...)
                  organizations and proper nouns

Another big differentiator is custom named entity recognition (CNER) for industry verticals. Take Healthcare for example. We can design and develop CNERs for Physician, Prescription, etc. Then they can be added to queries like 
     > what patients are still waiting for appointments PHYSICIAN:"John Smith"
     > who has had the best outcomes SCRIPT:mylodextrin

This can be developed for any of the verticals our customers work in. 
EnterpriseNLP is easy to install with your existing search technology or let us provide a complete solution based on Solr. With state of the art natural language processing and analytics we can help your employees find the right information quickly and powerfully.

Competitive Analysis:
While many of the Big Tech companies provide cloud based NLP services, they don't actually provide enterprise NLP based search. For example, Google's NLP offering offers sentiment analysis and named entity extraction but not NLP search. Amazon's NLP offering - Comprehend - also does not provide enterprise search. Instead "Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to find insights and relationships in text". Amazon's newest offering "Kendra" appears to have errors in their search technology.

Microsoft Azure is now declaring they have "cognitive search" but they only offer simple named entity extraction. It's miles from an actual cognitive search implementation. Don't be fooled.

For many companies with huge numbers of documents, the time and cost of uploading all of them to the cloud would be excessive.  Another drawback of the "just load your documents into our cloud" is the security/sensitivity issue.  Keeping your sensitive documents within your own enterprise is a more secure option, and that's exactly what Noonean EnterpriseNLP supports.

In Summary:

EnterpriseNLP is the most sophisticated and advanced technology on the market today and we achieve the best performance and accuracy of any tool - returning results in just milliseconds. How much will your company save by having the right information at your employees fingertips. How much will your administrators save by having a much simpler solution to enterprise search?

Try EnterpriseNLP - the search technology for innovative companies. Contact Us Today!